U.S. patent application number 13/077035 was filed with the patent office on 2012-03-22 for p2p real time media recommendations.
This patent application is currently assigned to NAPO ENTERPRISES, LLC. Invention is credited to Hugh Svendsen.
Application Number | 20120072610 13/077035 |
Document ID | / |
Family ID | 40137477 |
Filed Date | 2012-03-22 |
United States Patent
Application |
20120072610 |
Kind Code |
A1 |
Svendsen; Hugh |
March 22, 2012 |
P2P REAL TIME MEDIA RECOMMENDATIONS
Abstract
Systems and methods are described for providing peer-to-peer
(P2P) media recommendations. In one embodiment, a central streaming
media service operates to stream media presentations to user
devices of users. For each user desiring to send and receive
recommendations, each time a media presentation is streamed to and
played by a user device of the user, the central media service
provides a recommendation identifying the media presentation to one
or more other users associated with the user. Similarly, the
central media service provides media recommendations to the user
from one or more other users. Once streaming and playback of the
media presentation is complete or substantially complete, the
central streaming media service automatically selects a next media
presentation for the user from a group of media presentations
including those identified by the recommendations provided to the
user and begins streaming the next media presentation to the user
device of the user.
Inventors: |
Svendsen; Hugh; (Chapel
Hill, NC) |
Assignee: |
NAPO ENTERPRISES, LLC
Wilmington
DE
|
Family ID: |
40137477 |
Appl. No.: |
13/077035 |
Filed: |
March 31, 2011 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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12195628 |
Aug 21, 2008 |
7970922 |
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13077035 |
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11484130 |
Jul 11, 2006 |
7680959 |
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12195628 |
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Current U.S.
Class: |
709/231 |
Current CPC
Class: |
H04L 12/1859 20130101;
G06Q 30/0631 20130101; H04N 7/00 20130101; H04L 29/00 20130101;
H04N 7/17318 20130101; G06Q 30/0201 20130101; H04L 67/104 20130101;
H04N 21/8113 20130101; G06Q 30/0282 20130101; H04L 12/1822
20130101; G06Q 30/02 20130101; H04N 21/4788 20130101; H04N 21/4826
20130101; H04L 12/2803 20130101; H04N 21/4825 20130101; H04L 12/00
20130101; H04N 21/4661 20130101 |
Class at
Publication: |
709/231 |
International
Class: |
G06F 15/16 20060101
G06F015/16 |
Claims
1. A method of operation of a central streaming media service
comprising: streaming a media presentation to a user device of a
first user for playback; automatically providing a media
recommendation identifying the media presentation to a second user
in response to playback of the media presentation at the user
device of the first user; receiving the media recommendation on
behalf of the second user; automatically adding the media
presentation identified by the media recommendation to a
pre-existing list of media presentations maintained for the second
user to provide an updated list of media presentations for the
second user; automatically selecting a select media presentation to
stream to a user device of the second user from the updated list of
media presentations for the second user based on user preferences
of the second user; and streaming the select media presentation to
the user device of the second user for playback.
2. The method of claim 1 wherein automatically providing the media
recommendation comprises automatically providing the media
recommendation identifying the media presentation to the second
user upon initiation of playback of the media presentation at the
user device of the first user.
3. The method of claim 1 wherein automatically providing the media
recommendation comprises automatically providing the media
recommendation identifying the media presentation to the second
user upon completion of playback of a threshold amount of the media
presentation at the user device of the first user.
4. The method of claim 1 wherein automatically providing the media
recommendation comprises automatically providing the media
recommendation identifying the media presentation to the second
user upon completion of playback of the media presentation at the
user device of the first user.
5. The method of claim 1 wherein automatically providing the media
recommendation identifying the media presentation to the second
user comprises automatically providing the media recommendation
identifying the media presentation to a data structure associated
with the second user.
6. The method of claim 1 wherein automatically providing the media
recommendation identifying the media presentation to the second
user comprises automatically providing the media recommendation
identifying the media presentation to a component of the central
streaming media service responsible for receiving media
recommendations sent to the second user.
7. The method of claim 1 wherein the pre-existing list comprises
one or more media presentations identified by a corresponding one
or more media recommendations sent to the second user.
8. The method of claim 1 wherein the pre-existing list comprises
one or more media presentations selected by the second user.
9. The method of claim 1 wherein the pre-existing list comprises
one or more media presentations identified by the central streaming
media service.
10. The method of claim 1 wherein the media presentation identified
by the media recommendation is a song.
11. The method of claim 1 wherein the media presentation identified
by the media recommendation is a video presentation.
12. The method of claim 1 wherein the media presentation identified
by the media recommendation is an audio presentation.
13. The method of claim 1 wherein each media presentation in the
pre-existing list of media presentations is scored, and the method
further comprises: scoring the media presentation identified by the
media recommendation based on the user preferences of the second
user; wherein automatically selecting the select media presentation
to stream to the user device of the second user comprises
automatically selecting the select media presentation from the
updated list of media presentations based on scores assigned to the
media presentations, including the media presentation identified by
the media recommendation, in the updated list of media
presentations.
14. The method of claim 13 wherein the user preferences of the
second user comprise weights assigned to a plurality of categories,
and scoring the media presentation identified by the media
recommendation comprises: identifying one of the plurality of
categories applicable to the media presentation identified by the
media recommendation; and scoring the media presentation identified
by the media recommendation based on the weight assigned to the one
of the plurality of categories.
15. The method of claim 14 wherein the plurality of categories
comprises one or more categories selected from a group consisting
of: recommending user, genre, decade, and availability.
16. The method of claim 14 wherein the user preferences of the
second user further comprise weights assigned to a plurality of
possible attributes for each of the plurality of categories, and
scoring the media presentation identified by the media
recommendation comprises: identifying one of the plurality of
categories applicable to the media presentation identified by the
media recommendation; identifying one of the plurality of possible
attributes for the one of the plurality of categories applicable to
the media presentation identified by the media recommendation; and
scoring the media presentation identified by the media
recommendation based on the weight assigned to the one of the
plurality of categories and the weight assigned to the one of the
plurality of possible attributes for the one of the plurality of
categories.
17. The method of claim 14 wherein the user preferences of the
second user further comprise weights assigned to a plurality of
other users including the second user, and scoring the media
presentation identified by the media recommendation comprises
scoring the media presentation identified by the media
recommendation based on a weight assigned to the second user.
18. The method of claim 14 wherein the user preferences of the
second user further comprise weights assigned to a plurality of
media presentation attributes, and scoring the media presentation
identified by the media recommendation comprises: identifying one
or more of the plurality of media presentation attributes
applicable to the media presentation identified by the media
recommendation; and scoring the media presentation identified by
the media recommendation based on the weights assigned to the one
or more of the plurality of media presentation attributes
applicable to the media presentation identified by the media
recommendation.
19. The method of claim 18 wherein the plurality of media
presentation attributes comprises at least one of a group
consisting of: a plurality of music genres and a plurality of time
periods.
20. The method of claim 14 wherein automatically selecting the
select media presentation from the updated list of media
presentations based on the scores assigned to the media
presentations, including the media presentation identified by the
media recommendation, in the updated list of media presentations
comprises: sorting the updated list of media presentations based on
the scores to provide a sorted list of media presentations; and
automatically selecting a media presentation from the sorted list
of media presentations having a most preferred score as the select
media presentation to stream to the user device of the second user
for playback.
21. The method of claim 1 wherein the central streaming media
service is a subscription-based service.
22. The method of claim 1 further comprising automatically
obtaining rights for the second user to access the select media
presentation if the second user does not have access rights to the
select media presentation.
23. The method of claim 1 wherein streaming the select media
presentation comprises: streaming a preview of the select media
presentation to the user device of the second user if the second
user does not have access rights to the select media presentation;
and streaming a complete version of the select media presentation
to the user device of the second user if the second user has access
rights to the select media presentation.
24. The method of claim 1 further comprising: making a
determination as to whether the media recommendation is to be
filtered based on one or more criterion; wherein the steps of
automatically adding the media presentation identified by the media
recommendation to the pre-existing list of media presentations
maintained for the second user to provide the updated list of media
presentations for the second user, automatically selecting the
select media presentation to stream to the user device of the
second user from the updated list of media presentations for the
second user based on the user preferences of the second user, and
streaming the select media presentation to the user device of the
second user for playback are performed if the determination is made
not to filter the media recommendation.
25. The method of claim 1 wherein: receiving the media
recommendation comprises receiving the media recommendation during
streaming of a first media presentation to the user device of the
second user for playback; and streaming the select media
presentation to the user device of the second user comprises
streaming the select media presentation to the user device of the
second user for playback in such a manner that enables playback of
the select media presentation to begin upon completion of playback
of the first media presentation.
26. A central server hosting a central streaming media service,
comprising: a communication interface communicatively coupling the
central server to a network; and a control system associated with
the communication interface and adapted to: stream a media
presentation to a user device of a first user via the network for
playback; automatically provide a media recommendation identifying
the media presentation to a second user in response to playback of
the media presentation at the user device of the first user;
receive the media recommendation on behalf of the second user;
automatically add the media presentation identified by the media
recommendation to a pre-existing list of media presentations
maintained for the second user to provide an updated list of media
presentations for the second user; automatically select a select
media presentation to stream to a user device of the second user
from the updated list of media presentations for the second user
based on user preferences of the second user; and stream the select
media presentation to the user device of the second user via the
network for playback.
27. The central server of claim 26 wherein in order to
automatically provide the media recommendation identifying the
media presentation to the second user, the control system is
adapted to automatically provide the media recommendation
identifying the media presentation to a data structure associated
with the second user.
28. The central server of claim 26 wherein in order to
automatically provide the media recommendation identifying the
media presentation to the second user, the control system is
adapted to automatically provide the media recommendation
identifying the media presentation to a component of the control
system that automatically adds the media presentation identified by
the media recommendation to the pre-existing list of media
presentations maintained for the second user to provide the updated
list of media presentations for the second user.
29. A non-transitory computer readable medium storing software for
instructing a controller of a computing device to: stream a media
presentation to a user device of a first user via the network for
playback; automatically provide a media recommendation identifying
the media presentation to a second user in response to playback of
the media presentation at the user device of the first user;
receive the media recommendation on behalf of the second user;
automatically add the media presentation identified by the media
recommendation to a pre-existing list of media presentations
maintained for the second user to provide an updated list of media
presentations for the second user; automatically select a select
media presentation to stream to a user device of the second user
from the updated list of media presentations for the second user
based on user preferences of the second user; and stream the select
media presentation to the user device of the second user via the
network for playback.
30. The computer readable medium of claim 29 wherein in order to
automatically provide the media recommendation identifying the
media presentation to the second user, the control system is
adapted to automatically provide the media recommendation
identifying the media presentation to a data structure associated
with the second user.
31. The computer readable medium of claim 29 wherein in order to
automatically provide the media recommendation identifying the
media presentation to the second user, the control system is
adapted to automatically provide the media recommendation
identifying the media presentation to a component of the control
system that automatically adds the media presentation identified by
the media recommendation to the pre-existing list of media
presentations maintained for the second user to provide the updated
list of media presentations for the second user.
32. A method of operation of a central streaming media service
comprising: providing a list of media presentations for a user
comprising a first plurality of media presentations; automatically
providing a plurality of media recommendations to the user from a
plurality of recommenders, each of the plurality of media
recommendations automatically provided in response to playback of a
corresponding one of a second plurality of media presentations at
the user device of a corresponding one of the plurality of
recommenders; receiving the plurality of media recommendations on
behalf of the user; automatically adding the second plurality of
media presentations identified by the plurality of media
recommendations to the list of media presentations maintained for
the user to provide an updated list of media presentations for the
user; automatically selecting a select media presentation to stream
to a user device of the user from the updated list of media
presentations for the user based on user preferences of the user;
and streaming the select media presentation to the user device of
the user for playback.
33. The method of claim 32 wherein automatically providing the
plurality of media recommendations to the user comprises
automatically providing the plurality of media recommendations to a
data structure associated with the user.
34. The method of claim 32 wherein automatically providing the
plurality of media recommendations to the user comprises
automatically providing the plurality of media recommendations to a
component of the central streaming media service responsible for
receiving the plurality of media recommendations on behalf of the
user.
Description
RELATED APPLICATIONS
[0001] This application is a continuation of U.S. patent
application Ser. No. 12/195,628, filed on Aug. 21, 2008, entitled
P2P REAL TIME MEDIA RECOMMENDATIONS, which is a
continuation-in-part of U.S. patent application Ser. No.
11/484,130, filed on Jul. 11, 2006, entitled P2P NETWORK FOR
PROVIDING REAL TIME MEDIA RECOMMENDATIONS, now U.S. Pat. No.
7,680,959, the disclosures of both are hereby incorporated herein
by reference in their entireties.
FIELD OF THE DISCLOSURE
[0002] The present disclosure relates to media recommendations,
such as music or video recommendations, and more specifically
relates to peer-to-peer (P2P) real time media recommendations.
BACKGROUND
[0003] In recent years, there has been an enormous increase in the
amount of digital media, such as music, available online. Services,
such as Apple's iTunes Music Store.RTM. service, enable users to
legally purchase and download music. Other services such as
Yahoo!.RTM. Music Unlimited and RealNetwork's Rhapsody provide
access to millions of songs for a monthly subscription fee. As a
result, music has become much more accessible to listeners
worldwide. However, the increased accessibility of music has only
heightened a long-standing problem for the music industry, which is
namely the issue of linking audiophiles with new music that matches
their listening preferences.
[0004] Many companies, technologies, and approaches have emerged to
address this issue of music recommendation. Some companies have
taken an analytical approach. They review various attributes of a
song, such as melody, harmony, lyrics, orchestration, vocal
character, and the like, and assign a rating to each attribute. The
ratings for each attribute are then assembled to create a holistic
classification for the song that is then used by a recommendation
engine. The recommendation engine typically requires that the user
first identify a song that he or she likes. The recommendation
engine then suggests other songs with similar attributions.
Companies using this type of approach include Pandora, SoundFlavor,
MusicIP, and MongoMusic (purchased by Microsoft in 2000).
[0005] Other companies take a communal approach. They make
recommendations based on the collective wisdom of a group of users
with similar musical tastes. These solutions first profile the
listening habits of a particular user and then search similar
profiles of other users to determine recommendations. Profiles are
generally created in a variety of ways such as looking at a user's
complete collection, the playcounts of their songs, their favorite
playlists, and the like. Companies using this technology include
Last.fm, Music Strands, WebJay, Mercora, betterPropaganda, Loomia,
eMusic, musicmatch, genielab, upto11, Napster, and iTunes with its
celebrity playlists.
[0006] The problem with these traditional recommendation systems is
that they fail to consider peer influences. For example, the music
that a particular teenager listens to may be highly influenced by
the music listened to by a group of the teenager's peers, such as
his or her friends. As such, there is a need for a music
recommendation system and method that recommends music to a user
based on the listening habits of a peer group.
SUMMARY
[0007] The present disclosure relates to systems and methods for
providing peer-to-peer (P2P) media recommendations in real-time, or
substantially real-time. The media recommendations may be, for
example, song recommendations or video recommendations. In one
embodiment, a central streaming media service operates to stream
media presentations to user devices of users registered with the
central streaming media service. For each user desiring to send and
receive media recommendations, each time a media presentation is
streamed to and played by a user device of the user, the central
streaming media service provides a media recommendation identifying
the media presentation to one or more other users associated with
the user. In addition, while the media presentation is being
streamed to and played by the user device of the user, the central
streaming media service provides media recommendations to the user
from one or more other users in response to corresponding media
presentations being streamed to and played by the one or more other
users. Once streaming and playback of the media presentation is
complete or substantially complete, the central streaming media
service automatically selects a next media presentation to be
streamed to and played by the user device of the user from a group
of media presentations including the media presentations identified
by the media recommendations provided to the user. Once the next
media presentation is selected, the central streaming media service
begins streaming the selected media presentation to the user device
of the user.
[0008] Those skilled in the art will appreciate the scope of the
present disclosure and realize additional aspects thereof after
reading the following detailed description of the preferred
embodiments in association with the accompanying drawing
figures.
BRIEF DESCRIPTION OF THE DRAWING FIGURES
[0009] The accompanying drawing figures incorporated in and forming
a part of this specification illustrate several aspects of the
disclosure, and together with the description serve to explain the
principles of the disclosure.
[0010] FIG. 1 illustrates a system incorporating a peer-to-peer
(P2P) network for real time media recommendations according to one
embodiment of the present disclosure;
[0011] FIG. 2 is a flow chart illustrating the operation of the
peer devices of FIG. 1 according to one embodiment of the present
disclosure;
[0012] FIG. 3 illustrates the operation of the system of FIG. 1
according to one embodiment of the present disclosure;
[0013] FIG. 4 illustrates a system incorporating a P2P network for
real time media recommendations according to a second embodiment of
the present disclosure;
[0014] FIG. 5 illustrates the operation of the system of FIG. 4
according to one embodiment of the present disclosure;
[0015] FIG. 6 is a flow chart illustrating a method for
automatically selecting media to play based on recommendations from
peer devices and user preferences according to one embodiment of
the present disclosure;
[0016] FIG. 7 illustrates an exemplary graphical user interface
(GUI) for configuring user preferences according to one embodiment
of the present disclosure;
[0017] FIG. 8 illustrates an exemplary GUI for assigning weights to
various categories of media content as part of configuring the user
preferences according to one embodiment of the present
disclosure;
[0018] FIG. 9 illustrates an exemplary GUI for assigning weights to
individual users within a user category as part of configuring the
user preferences according to one embodiment of the present
disclosure;
[0019] FIG. 10 illustrates an exemplary GUI for assigning weights
to individual genres from a genre category as part of configuring
the user preferences according to one embodiment of the present
disclosure;
[0020] FIG. 11 illustrates an exemplary GUI for assigning weights
to individual decades from a decade category as part of configuring
the user preferences according to one embodiment of the present
disclosure;
[0021] FIG. 12 illustrates an exemplary GUI for assigning weights
to individual availability types from an availability type category
as part of configuring the user preferences according to one
embodiment of the present disclosure;
[0022] FIG. 13 illustrates an exemplary GUI displaying a playlist
including both songs from a local music collection of a peer device
and recommended songs from other peer devices, where the songs are
sorted by a score determined based on user preferences according to
one embodiment of the present disclosure;
[0023] FIG. 14 illustrates an exemplary GUI displaying a playlist
including both songs from a local music collection of a peer device
and recommended songs from other peer devices, where the songs are
sorted by a both genre and score according to one embodiment of the
present disclosure;
[0024] FIG. 15 is a block diagram of a peer device of FIG. 1
according to one embodiment of the present disclosure;
[0025] FIG. 16 is a block diagram of a peer device of FIG. 4
according to one embodiment of the present disclosure;
[0026] FIG. 17 illustrates a system for providing P2P media
recommendations according to another embodiment of the present
disclosure;
[0027] FIG. 18 is a flow chart illustrating the operation of a
streaming and recommendation function of the central media service
of FIG. 17 according to one embodiment of the present
disclosure;
[0028] FIG. 19 is a more detailed flow chart illustrating the
operation of the streaming and recommendation function of the
central media service of FIG. 17 according to one embodiment of the
present disclosure;
[0029] FIG. 20 is a block diagram of the central server of FIG. 17
according to one embodiment of the present disclosure; and
[0030] FIG. 21 is a block diagram of one of the user devices of
FIG. 17 according to one embodiment of the present disclosure.
DETAILED DESCRIPTION
[0031] The embodiments set forth below represent the necessary
information to enable those skilled in the art to practice the
embodiments and illustrate the best mode of practicing the
embodiments. Upon reading the following description in light of the
accompanying drawing figures, those skilled in the art will
understand the concepts of the disclosure and will recognize
applications of these concepts not particularly addressed herein.
It should be understood that these concepts and applications fall
within the scope of the disclosure and the accompanying claims.
[0032] FIG. 1 illustrates a system 10 incorporating a P2P network
for providing real time song recommendations according to one
embodiment of the present disclosure. Note that while the
discussion herein focuses on song recommendations for clarity and
ease of discussion, the present disclosure is equally applicable to
providing recommendations for other types of media presentations
such as video presentations, as will be apparent to one of ordinary
skill in the art upon reading this disclosure. Exemplary video
presentations are movies, television programs, and the like. In
general, the system 10 includes a number of peer devices 12-16
which are optionally connected to a subscription music service 18
via a network 20, which may be a distributed public network such
as, but not limited to, the Internet. Note that while three peer
devices 12-16 are illustrated, the present disclosure may be used
with any number of two or more peer devices.
[0033] In this embodiment, the peer devices 12-16 are preferably
portable devices such as, but not limited to, portable audio
players, mobile telephones, Personal Digital Assistants (PDAs), or
the like having audio playback capabilities. However, the peer
devices 12-16 may alternatively be stationary devices such as a
personal computer or the like. The peer devices 12-16 include local
wireless communication interfaces (FIG. 15) communicatively
coupling the peer devices 12-16 to form a peer-to-peer (P2P)
network. The wireless communication interfaces may provide wireless
communication according to, for example, one of the suite of IEEE
802.11 standards, the Bluetooth standard, or the like.
[0034] The peer device 12 includes a music player 22, a
recommendation engine 24, and a music collection 26. The music
player 22 may be implemented in software, hardware, or a
combination of hardware and software. In general, the music player
22 operates to play songs from the music collection 26. The
recommendation engine 24 may be implemented in software, hardware,
or a combination of hardware and software. The recommendation
engine 24 may alternatively be incorporated into the music player
22. The music collection 26 includes any number of song files
stored in one or more digital storage units such as, for example,
one or more hard-disc drives, one or more memory cards, internal
Random-Access Memory (RAM), one or more associated external digital
storage devices, or the like.
[0035] In operation, each time a song is played by the music player
22, the recommendation engine 24 operates to provide a
recommendation identifying the song to the other peer devices 14,
16 via the P2P network. The recommendation does not include the
song. In one embodiment, the recommendation may be a recommendation
file including information identifying the song. In addition, as
discussed below in detail, the recommendation engine 24 operates to
programmatically, or automatically, select a next song to be played
by the music player 22 based on the recommendations received from
the other peer device 14, 16 identifying songs recently played by
the other peer devices 14, 16 and user preferences associated with
the user of the peer device 12.
[0036] Like the peer device 12, the peer device 14 includes a music
player 28, a recommendation engine 30, and a music collection 32,
and the peer device 16 includes a music player 34, a recommendation
engine 36, and a music collection 38.
[0037] The subscription music service 18 may be a service hosted by
a server connected to the network 20. Exemplary subscription based
music services that may be modified to operate according to the
present disclosure are Yahoo! Music Unlimited digital music service
and RealNetwork's Rhapsody digital music service.
[0038] FIG. 2 illustrates the operation of the peer device 12
according to one embodiment of the present disclosure. However, the
following discussion is equally applicable to the other peer
devices 14, 16. First, the peer devices 12-16 cooperate to
establish a P2P network (step 200). The P2P network may be
initiated using, for example, an electronic or verbal invitation.
Invitations may be desirable when the user wishes to establish the
P2P network with a particular group of other users, such as his or
her friends. Note that this may be beneficial when the user desires
that the music he or she listens to be influenced only by the songs
listened to by, for example, the user's friends. Invitations may
also be desirable when the number of peer devices within a local
wireless coverage area of the peer device 12 is large. As another
example, the peer device 12 may maintain a "buddy list" identifying
friends of the user of the peer device 12, where the peer device 12
may automatically establish a P2P network with the peer devices of
the users identified by the "buddy list" when the peer devices are
within a local wireless coverage area of the peer device 12.
[0039] Alternatively, the peer device 12 may establish an ad-hoc
P2P network with the other peer devices 14, 16 by detecting the
other peer devices 14, 16 within the local wireless coverage area
of the peer device 12 and automatically establishing the P2P
network with at least a subset of the detected peer devices 14, 16.
In order to control the number of peer devices within the ad-hoc
P2P network, the peer device 12 may compare user profiles of the
users of the other peer devices 14, 16 with a user profile of the
user of the peer device 12 and determine whether to permit the
other peer devices 14, 16 to enter the P2P network based on the
similarities of the user profiles.
[0040] At some point after the P2P network is established, the peer
device 12 plays a song (step 202). Initially, before any
recommendations have been received from the other peer devices 14,
16, the song may be a song from the music collection 26 selected by
the user of the peer device 12. Prior to, during, or after playback
of the song, the recommendation engine 24 sends a recommendation
identifying the song to the other peer devices 14, 16 (step 204).
The recommendation may include, but is not limited to, information
identifying the song such as a Globally Unique Identifier (GUID)
for the song, title of the song, or the like; a Uniform Resource
Locator (URL) enabling other peer devices to obtain the song such
as a URL enabling download or streaming of the song from the
subscription music service 18 or a URL enabling purchase and
download of the song from an e-commerce service; a URL enabling
download or streaming of a preview of the song from the
subscription music service 18 or a similar e-commerce service;
metadata describing the song such as ID3 tags including, for
example, genre, the title of the song, the artist of the song, the
album on which the song can be found, the date of release of the
song or album, the lyrics, and the like.
[0041] The recommendation may also include a list of recommenders
including information identifying each user having previously
recommended the song and a timestamp for each recommendation. For
example, if the song was originally played at the peer device 14
and then played at the peer device 16 in response to a
recommendation from the peer device 14, the list of recommenders
may include information identifying the user of the peer device 14
or the peer device 14 and a timestamp identifying a time at which
the song was played or recommended by the peer device 14, and
information identifying the user of the peer device 16 or the peer
device 16 and a timestamp identifying a time at which the song was
played or recommended by the peer device 16. Likewise, if the peer
device 12 then selects the song for playback, information
identifying the user of the peer device 12 or the peer device 12
and a corresponding timestamp may be appended to the list of
recommenders.
[0042] The peer device 12, and more specifically the recommendation
engine 24, also receives recommendations from the other peer
devices 14, 16 (step 206). The recommendations from the other peer
devices 14, 16 identify songs played by the other peer devices 14,
16. Optionally, the recommendation engine 24 may filter the
recommendations from the other peer devices 14, 16 based on, for
example, user, genre, artist, title, album, lyrics, date of
release, or the like (step 208).
[0043] The recommendation engine 24 then automatically selects a
next song to play from the songs identified by the recommendations
received from the other peer devices 14, 16, optionally songs
identified by previously received recommendations, and one or more
songs from the music collection 26 based on user preferences (step
210). In one embodiment, the recommendation engine 24 considers
only those songs identified by recommendations received since a
previous song selection. For example, if the song played in step
202 was a song selected by the recommendation engine 24 based on
prior recommendations from the peer devices 14, 16, the
recommendation engine 24 may only consider the songs identified in
new recommendations received after the song was selected for
playback in step 202 and may not consider the songs identified in
the prior recommendations. This may be beneficial if the complexity
of the recommendation engine 24 is desired to be minimal such as
when the peer device 12 is a mobile terminal or the like having
limited processing and memory capabilities. In another embodiment,
the recommendation engine 24 may consider all previously received
recommendations, where the recommendations may expire after a
predetermined or user defined period of time.
[0044] As discussed below, the user preferences used to select the
next song to play may include a weight or priority assigned to each
of a number of categories such as user, genre, decade of release,
and availability. Generally, availability identifies whether songs
are stored locally in the music collection 26; available via the
subscription music service 18; available for download, and
optionally purchase, from an e-commerce service or one of the other
peer devices 14, 16; or are not currently available where the user
may search for the songs if desired. The user preferences may be
stored locally at the peer device 12 or obtained from a central
server via the network 20. If the peer device 12 is a portable
device, the user preferences may be configured on an associated
user system, such as a personal computer, and transferred to the
peer device 12 during a synchronization process. The user
preferences may alternatively be automatically provided or
suggested by the recommendation engine 24 based on a play history
of the peer device 12. In the preferred embodiment discussed below,
the songs identified by the recommendations from the other peer
devices 14, 16 and the songs from the music collection 26 are
scored or ranked based on the user preferences. Then, based on the
scores, the recommendation engine 24 selects the next song to
play.
[0045] Once the next song to play is selected, the peer device 12
obtains the selected song (step 212). If the selected song is part
of the music collection 26, the peer device 12 obtains the selected
song from the music collection 26. If the selected song is not part
of the music collection 26, the recommendation engine 24 obtains
the selected song from the subscription music service 18, an
e-commerce service, or one of the other peer devices 14, 16. For
example, the recommendation for the song may include a URL
providing a link to a source from which the song may be obtained,
and the peer device 12 may obtain the selected song from the source
identified in the recommendation for the song. Once obtained, the
selected song is played and the process repeats (steps
202-212).
[0046] FIG. 3 illustrates the operation of the peer devices 12-16
to provide real time song recommendations according to one
embodiment of the present disclosure. The illustrated process is
the same as discussed above with respect to FIG. 2. As such, the
details will not be repeated. In general, the peer devices 14, 16
play songs and, in response, provide song recommendations to the
peer device 12 (steps 300-306). The peer device 12 may optionally
filter the recommendations from the peer devices 14, 16 (step 308).
The recommendation engine 24 of the peer device 12 then
automatically selects the next song to play from the songs
identified by the recommendations, optionally songs identified by
prior recommendations from the peer devices 14, 16, and locally
stored songs from the music collection 26 based on user preferences
of the user of the peer device 12 (step 310). The peer device 12
then obtains and plays the selected song (steps 312-314). Either
prior to, during, or after playback of the selected song, the
recommendation engine 24 of the peer device 12 provides a
recommendation identifying the selected song to the other peer
devices 14, 16 (step 316-318).
[0047] FIG. 4 illustrates the system 10' according to second
embodiment of the present disclosure. In this embodiment, the peer
devices 12'-16' form a P2P network via the network 20 and a proxy
server 40. The peer devices 12'-16' may be any device having a
connection to the network 20 and audio playback capabilities. For
example, the peer devices 12'-16' may be personal computers, laptop
computers, mobile telephones, portable audio players, PDAs, or the
like having either a wired or wireless connection to the network
20. As discussed above with respect to the peer device 12, the peer
device 12' includes music player 22', a recommendation engine 24',
and a music collection 26'. Likewise, the peer device 14' includes
a music player 28', a recommendation engine 30', and a music
collection 32', and the peer device 16' includes a music player
34', a recommendation engine 36', and a music collection 38.
[0048] FIG. 5 illustrates the operation of the system 10' of FIG.
4. Prior to beginning the process, the peer devices 12'-16' form a
P2P network. Since the number of peer devices 12'-16' that may be
connected to the network 20 may be very large, the peer devices
12'-16' may implement some technique for identifying a desired
group of peer devices for the P2P network. For example, the P2P
network may be initiated using, for example, an electronic or
verbal invitation. As another example, the peer device 12' may
maintain a "buddy list" identifying friends of the user of the peer
device 12', where the peer device 12' may automatically establish a
P2P network with the peer devices of the users identified by the
"buddy list" when the peer devices are connected to the network 20.
Alternatively, the peer devices 12'-16' may form an ad-hoc network
where the participants for the ad-hoc network are selected based on
similarities in user profiles.
[0049] In this example, once the P2P network is established, the
peer device 14' plays a song and, in response, provides a song
recommendation identifying the song to the peer device 12' via the
proxy server 40 (steps 400-404). While not illustrated for clarity,
the peer device 14' also sends the recommendation for the song to
the peer device 16' via the proxy server 40. The peer device 16'
also plays a song and sends a song recommendation to the peer
device 12' via the proxy server 40 (steps 406-410). Again, while
not illustrated for clarity, the peer device 16' also sends the
recommendation for the song to the peer device 14' via the proxy
server 40.
[0050] From this point, the process continues as discussed above.
More specifically, the recommendation engine 24' may optionally
filter the recommendations from the other peer devices 14', 16'
based on, for example, user, genre, artist, title, album, lyrics,
date of release, or the like (step 412). The recommendation engine
24' then automatically selects a next song to play from the songs
identified by the recommendations received from the other peer
devices 14'-16', optionally songs identified by previously received
recommendations from the peer devices 14'-16', and one or more
songs from the music collection 26' based on user preferences (step
414). In the preferred embodiment discussed below, the songs
identified by the recommendations from the other peer devices
14'-16' and the songs from the music collection 26' are scored
based on the user preferences. Then, based on the scores, the
recommendation engine 24' selects the next song to play.
[0051] Once the next song to play is selected, the peer device 12'
obtains the selected song (step 416). If the selected song is part
of the music collection 26', the peer device 12' obtains the
selected song from the music collection 26'. If the selected song
is not part of the music collection 26', the recommendation engine
24' obtains the selected song from the subscription music service
18, an e-commerce service, or one of the other peer devices
14'-16'. For example, the selected song may be obtained from a
source identified in the recommendation for the song. Once
obtained, the selected song is played and a recommendation for the
song is provided to the other peer devices 14'-16' via the proxy
server 40 (steps 418-426). Note that while FIG. 5 illustrates two
separate song recommendation files sent from the peer device 12' to
the proxy server 40, the present disclosure is not limited thereto.
One of ordinary skill in the art will appreciate that a single song
recommendation file may be provided from the peer device 12' to the
proxy server 40. The proxy server 40 may then forward the song
recommendation file to the peer devices 14' and 16'.
[0052] FIG. 6 illustrates the process of automatically selecting a
song to play from the received recommendations and locally stored
songs at the peer device 12' according to one embodiment of the
present disclosure. However, the following discussion is equally
applicable to the peer devices 12-16 of FIG. 1, as well as the
other peer devices 14'-16' of FIG. 4. First, the user preferences
for the user of the peer device 12' are obtained (step 500). The
user preferences may include a weight or priority assigned to each
of a number of categories such as, but not limited to, user, genre,
decade of release, and availability. The user preferences may be
obtained from the user during an initial configuration of the
recommendation engine 24'. In addition, the user preferences may be
updated by the user as desired. The user preferences may
alternatively be suggested by the recommendation engine 24' or the
proxy server 40 based on a play history of the peer device 12'.
Note that that proxy server 40 may ascertain the play history of
the peer device 12' by monitoring the recommendations from the peer
device 12' as the recommendations pass through the proxy server 40
on their way to the other peer devices 14'-16'. The user
preferences may be stored locally at the peer device 12' or
obtained from a central server, such as the proxy server 40, via
the network 20.
[0053] Once recommendations are received from the other peer
devices 14'-16', the recommendation engine 24' of the peer device
12' scores the songs identified by the recommendations based on the
user preferences (step 502). The recommendation engine 24' also
scores one or more local songs from the music collection 26' (step
504). The recommendation engine 24' then selects the next song to
play based, at least on part, on the scores of the recommended and
local songs (step 506).
[0054] FIG. 7 illustrates an exemplary graphical user interface
(GUI) 42 for configuring user preferences. First, the user assigns
a weight to various categories. In this example, the categories are
users, genre, decade, and availability. However, the present
disclosure is not limited thereto. The weights for the categories
may be assigned alphabetically by selecting radio button 44,
customized by the user by selecting radio button 46, or
automatically suggested based on a user profile of the user by
selecting radio button 48. If alphabetical weighting is selected,
the weights are assigned by alphabetically sorting the categories
and assigning a weight to each of the categories based on its
position in the alphabetically sorted list of categories. As
illustrated in FIG. 8, if customized weighting is selected, the
user may be presented with a GUI 50 for customizing the weighting
of the categories. As illustrated in the exemplary embodiment of
FIG. 8, the weights of the categories may be assigned by adjusting
corresponding sliding bars 52-58. Sliding bar 60 may be adjusted to
assign a weight to a "no repeat factor." The no repeat factor is a
dampening factor used to alter a song's score based on when the
song was previously played at the peer device 12' in order to
prevent the same song from being continually repeated.
[0055] Once the weights are assigned, the user may select an OK
button 62 to return to the GUI 42 of FIG. 7 or select a REVERT
button 64 to return the weights of the categories to their previous
settings. In addition, the user may select a SUGGEST FROM PROFILE
button 66 to have the recommendation engine 24' or the proxy server
40 suggest weights for the categories based on a user profile. Note
that the button 66 has the same effect as the radio button 48 of
FIG. 7.
[0056] Returning to FIG. 7, radio buttons 68-72 are used to select
a desired method for assigning weights to each user in the P2P
network, radio buttons 74-78 are used to select a desired method
for assigning weights to each of a number of genres of music, radio
buttons 80-84 are used to select the desired method for assigning
weights to each of a number of decades, and radio buttons 86-90 are
used to select the desired method for assigning weights to a number
of song availability types.
[0057] Regarding users, if the radio button 68 is selected, the
users are assigned weights based on their respective positions in
an alphabetically sorted list of users. If the radio button 70 is
selected, a GUI 92 (FIG. 9) enabling the user to customize the
weights assigned to a number of users from which recommendations
are received. An exemplary embodiment of the GUI 92 is illustrated
in FIG. 9, where sliding bars 94-98 enable the user to assign
customized weights to corresponding users. Returning to FIG. 7, if
the radio button 72 is selected, the recommendation engine 24' or
the proxy server 40 generates suggested weights for the users based
on a user profile associated with the peer device 12'.
[0058] Regarding genres, if the radio button 74 is selected, the
genres are assigned weights based on their respective positions in
an alphabetically sorted list of genres. If the radio button 76 is
selected, a GUI 100 (FIG. 10) enabling the user to customize the
weights assigned to a number of genres. An exemplary embodiment of
the GUI 100 is illustrated in FIG. 10, where sliding bars 102-116
enable the user to assign customized weights to corresponding
genres. Returning to FIG. 7, if the radio button 78 is selected,
the recommendation engine 24' or the proxy server 40 generates
suggested weights for the genres based on a user profile associated
with the peer device 12'.
[0059] Regarding decades, if the radio button 80 is selected, the
decades are assigned weights based on their respective positions in
a chronologically sorted list of decades. If the radio button 82 is
selected, a GUI 118 (FIG. 11) enabling the user to customize the
weights assigned to a number of decades. An exemplary embodiment of
the GUI 118 is illustrated in FIG. 11, where sliding bars 120-130
enable the user to assign customized weights to corresponding
decades. Returning to FIG. 7, if the radio button 84 is selected,
the recommendation engine 24' or the proxy server 40 generates
suggested weights for the decades based on a user profile
associated with the peer device 12'.
[0060] Regarding availability, if the radio button 86 is selected,
the availability types are assigned weights based on their
respective positions in an alphabetically sorted list of
availability types. If the radio button 88 is selected, a GUI 132
(FIG. 12) enabling the user to customize the weights assigned to a
number of availability types. An exemplary embodiment of the GUI
132 is illustrated in FIG. 12, where sliding bars 134-140 enable
the user to assign customized weights to corresponding availability
types. Returning to FIG. 7, if the radio button 90 is selected, the
recommendation engine 24' or the proxy server 40 generates
suggested weights for the availability types based on a user
profile associated with the peer device 12'.
[0061] An exemplary equation for scoring a particular song is:
Score=NRF(WUWUA+WGWGA+WDWDA+WAWAA)100,
where NRF is the "no repeat factor"; WU is the weight assigned to
the user category; WUA is the weight assigned to the user attribute
of the song, which is the user recommending the song; WG is the
weight assigned to the genre category; WGA is the weight assigned
to the genre attribute of the song, which is the genre of the song;
WD is the weight assigned to the decade category; WDA is the weight
assigned to the decade attribute of the song, which is the decade
in which the song or the album associated with the song was
released; WA is the weight assigned to the availability category;
and WAA is the weight assigned to the availability attribute of the
song, which is the availability of the song.
[0062] The NRF may, for example, be computed as:
NRF = MIN ( 10 NRFW , LASTREPEAT_INDEX ) 10 NRFW . ##EQU00001##
[0063] As an example, assume that the following category weights
have been assigned:
TABLE-US-00001 User Category 1 Genre Category 7 Decade Category 7
Availability Type Category 5 NRFW 9
Further assume that the attributes for the categories have been
assigned weights as follows:
TABLE-US-00002 User Genre Decade Availability User A 5 Alternative
8 1950s 2 Local 8 User B 5 Classic Rock 5 1960s 4 Subscription
Network 2 User C 5 Arena Rock 5 1970s 7 Buy/Download 1 Jazz 5 1980s
9 Find 1 New Wave 2 1990s 5 Punk 4 2000s 5 Dance 2 Country 2
Thus, if a particular song to be scored is recommended by the user
"User C," is from the "Alternative Genre," is from the "1980s"
decade, and is available from the subscription music service 18,
the score of the song may be computed as:
Score = NRF ( 1 20 5 10 + 7 20 8 10 + 7 20 9 10 + 5 20 2 10 ) 100
##EQU00002##
where if the song was last played 88 songs ago,
NRF = MIN ( 10 9 , 88 ) 10 9 = 88 90 . ##EQU00003##
Thus, the score for the song is
Score = 88 90 ( 1 20 5 10 + 7 20 8 10 + 7 20 9 10 + 5 20 2 10 ) 100
= 65.5 . ##EQU00004##
[0064] FIG. 13 is an exemplary GUI 142 showing a playlist for the
peer device 12' including both local and recommended songs
according to the present disclosure. However, note that a similar
list may be maintained internally by the peer device 12 of FIG. 1
and potentially optimized to display at least a portion of the GUI
142 on the display of the peer device 12. In this example, both the
local and recommended songs are scored, as described above, and
sorted according to their scores. In addition, as illustrated in
FIG. 14, the songs may be sorted based on another criterion, which
in the illustrated example is genre, and score.
[0065] The GUI 142 may optionally allow the user to block songs
having particular identified fields. In the examples of FIGS. 13
and 14, the user has identified the genre "country" and the artist
"iron maiden" as fields to be blocked, as illustrated by the
underlining. The user may select fields to block by, for example,
clicking on or otherwise selecting the desired fields. Songs having
the blocked fields are still scored but are not obtained or played
by the peer device 12'
[0066] In one embodiment, the recommendation engine 24' of the peer
device 12' may provide a download queue containing all songs to be
downloaded, and optionally purchased, from an external source such
as the subscription music service 18, an e-commerce service, or
another peer device 14'-16'. Songs in the download queue having
scores above a first predetermined or user defined threshold and
previews of other songs in the download queue having scores above a
second predetermined or user defined threshold but below the first
threshold may be automatically downloaded to the peer device
12'.
[0067] FIG. 15 is a block diagram of an exemplary embodiment of the
peer device 12 of FIG. 1. However, the following discussion is
equally applicable to the other peer devices 14, 16. In general,
the peer device 12 includes a control system 144 having associated
memory 146. In this example, the music player 22 and the
recommendation engine 24 are at least partially implemented in
software and stored in the memory 146. The peer device 12 also
includes a storage unit 148 operating to store the music collection
26 (FIG. 1). The storage unit 148 may be any number of digital
storage devices such as, for example, one or more hard-disc drives,
one or more memory cards, RAM, one or more external digital storage
devices, or the like. The music collection 26 may alternatively be
stored in the memory 146. The peer device 12 also includes a
communication interface 150. The communication interface 150
includes a local wireless communication interface for establishing
the P2P network with the other peer devices 14, 16. The local
wireless interface may operate according to, for example, one of
the suite of IEEE 802.11 standards, the Bluetooth standard, or the
like. The communication interface 150 may also include a network
interface communicatively coupling the peer device 12 to the
network 20 (FIG. 1). The peer device 12 also includes a user
interface 152, which may include components such as a display,
speakers, a user input device, and the like.
[0068] FIG. 16 is a block diagram of an exemplary embodiment of the
peer device 12' of FIG. 4. However, the following discussion is
equally applicable to the other peer devices 14'-16'. In general,
the peer device 12' includes a control system 154 having associated
memory 156. In this example, the music player 22' and the
recommendation engine 24' are at least partially implemented in
software and stored in the memory 156. The peer device 12' also
includes a storage unit 158 operating to store the music collection
26' (FIG. 4). The storage unit 158 may be any number of digital
storage devices such as, for example, one or more hard-disc drives,
one or more memory cards, RAM, one or more external digital storage
devices, or the like. The music collection 26' may alternatively be
stored in the memory 156. The peer device 12' also includes a
communication interface 160. The communication interface 160
includes a network interface communicatively coupling the peer
device 12' to the network 20 (FIG. 4). The peer device 12' also
includes a user interface 162, which may include components such as
a display, speakers, a user input device, and the like.
[0069] FIG. 17 illustrates a system 166 for providing P2P media
recommendations according to another embodiment of the present
disclosure. In general, the system 166 includes a central server
168 and a number of user devices 170-1 through 170-N having
associated users 172-1 through 172-N. The central server 168 and
the user devices 170-1 through 170-N are connected via a network
174 such as, for example, the Internet. However, the present
disclosure is not limited thereto. The network 174 may be any type
of Wide Area Network (WAN), Local Area Network (LAN), or the like,
or any combination thereof. Still further, the network 174 may
include wired components, wireless components, or a combination
thereof. Note that while a single central server 168 is illustrated
for clarity and ease of discussion, it will be readily apparent to
one having ordinary skill in the art upon reading this disclosure
that the system 166 may include multiple central servers 168 for
purposes of load balancing and redundancy.
[0070] The central server 168 includes a streaming media service
176, a user account repository 178, and a music repository 180. The
streaming media service 176 may be implemented in software,
hardware, or a combination thereof. In general, as discussed below,
the streaming media service 176 provides streaming of songs from
the music repository 180 to the user devices 170-1 through 170-N.
In addition, the streaming media service 176 exchanges P2P song
recommendations between the users 172-1 through 172-N in a manner
similar to that discussed above. Again, note that while the
discussion herein focuses on songs and song recommendations, the
present disclosure is not limited thereto. Other types of media
presentations may also be used.
[0071] The user account repository 178 includes a user account for
each of the users 172-1 through 172-N. Using the user 172-1 as an
example, the user account of the user 172-1 includes a list of
friends, or contacts, of the user 172-1. The "friends" of the user
172-1 are other users from the users 172-2 through 172-N that have
been identified as friends or contacts of the user 172-1. Note that
the manner in which the friends of the user 172-1 are identified is
not central to the present disclosure. Any appropriate manual or
automated technique may be used. For example, an invitation process
may be used. As another example, a profile matching process may be
used to select other users having user profiles (e.g.,
demographics, user preferences, play histories, or the like)
similar to that of the user 172-1 as friends of the user 172-1. In
addition, the user account of the user 172-1 includes user
preferences of the user 172-1. As discussed above, in one
embodiment, the user preferences of the user 172-1 include weights
assigned to each of a number of categories (e.g., genre, decade,
recommending user, availability, or the like) and, for each
category, weights assigned to a number of attributes within that
category (e.g., for the genre category, Rock, Metal, Alternative,
Country, Bluegrass, Jazz, or the like). The user account of the
user 172-1 may also include a user profile of the user 172-1. The
user profile may include demographic information describing the
user 172-1, a play history of the user 172-1, information
identifying media items in a media collection of the user 172-1
stored on the user device 170-1, statistical information describing
the media items in the media collection of the user 172-1, or the
like.
[0072] The music repository 180 includes a number of songs
available for streaming to the user devices 170-1 through 170-N. In
addition, the music repository 180 includes metadata describing
each of the songs. The metadata for a song may include, for
example, a title of the song, an artist of the song, an album on
which the song was released, a date of release, a genre of the
song, or the like.
[0073] In this embodiment, the streaming media service 176 includes
a number of streaming and recommendation functions 182-1 through
182-N corresponding to the users 172-1 through 172-N. Thus, for
example, the streaming and recommendation function 182-1 serves the
user 172-1, the streaming and recommendation function 182-2 serves
the user 172-2, etc. Note that the streaming and recommendation
functions 182-1 through 182-N are exemplary and are not intended to
limit the scope of the present disclosure. Numerous alternative
embodiments of the streaming media service 176 will be apparent to
one having ordinary skill in the art upon reading this disclosure.
In general, the streaming and recommendation functions 182-1
through 182-N operate to stream songs to the corresponding user
devices 170-1 through 170-N. In addition, the streaming and
recommendation functions 182-1 through 182-N send, receive, and
process song recommendations as discussed below.
[0074] Each of the user devices 170-1 through 170-N may be, for
example, a personal computer, a portable media player having
network capabilities, a mobile smart phone having media playback
capabilities, a set-top box, a gaming console having network and
media playback capabilities, or the like. The user devices 170-1
through 170-N include streaming clients 184-1 through 184-N,
respectively. The streaming clients 184-1 through 184-N may be
implemented in software, hardware, or a combination thereof. In
general, the streaming media clients 184-1 through 184-N provide
playback of streaming songs received from the central server 168.
In addition, the streaming media clients 184-1 through 184-N enable
the users 172-1 through 172-N to take desired actions during
playback such as pausing, fast-forwarding, rewinding, skipping from
one song to another, or the like.
[0075] FIG. 18 is a flow chart illustrating the operation of the
streaming and recommendation function 182-1 according to one
embodiment of the present disclosure. This discussion is equally
applicable to the other streaming and recommendation functions
182-2 through 182-N. First, the streaming and recommendation
function 182-1 identifies friends of the user 172-1 (step 600). The
friends of the user 172-1 may be manually identified by the user
172-1 using, for example, an invitation process. Alternatively, the
friends of the user 172-1 may be identified via an automatic
process. For example, the streaming and recommendation function
182-1 may identify other users having user profiles (e.g.,
demographic information) and/or user preferences that match that of
the user 172-1 to at least a threshold degree as friends for the
user 172-1.
[0076] Next, the streaming and recommendation function 182-1
streams a song to the user device 170-1 of the user 172-1 (step
602). In the preferred embodiment, the streaming and recommendation
function 182-1 maintains a list of songs, such as a playlist, for
the user 172-1. As discussed above, the list of songs includes
songs identified by song recommendations received from other users
identified as friends of the user 172-1. In addition, the list of
songs may include one or more songs selected by the user 172-1.
Still further, the list may include one or more songs selected or
recommended by the streaming media service 176 such as, for
example, the Top 10 songs from the Billboard charts, one or more of
the songs most played by the users 172-1 through 172-N, or the
like. Thus, for this first iteration, the user 172-1 may select a
song from the list to play. In response, the streaming and
recommendation function 182-1 begins streaming the selected song to
the user device 170-1 of the user 172-1 for playback.
[0077] In response to streaming the song to the user device 170-1
and playback of the song at the user device 170-1, the streaming
and recommendation function 182-1 sends a song recommendation
identifying the song to one or more other users identified as
friends of the user 172-1 (step 604). The song recommendation
includes information identifying the song such as, for example, a
GUID of the song, a reference (e.g., URL) to the song in the music
repository 180, a title of the song, or the like. The streaming and
recommendation function 182-1 may send the recommendation
substantially immediately and automatically upon initiation of
playback of the song, upon completion of playback of a threshold
amount of the song, or after completion of playback of the
song.
[0078] In one embodiment, in order to send the song recommendation
to the other users identified as friends of the user 172-1, the
streaming and recommendation function 182-1 sends the song
recommendation to corresponding ones of the streaming and
recommendation functions 182-2 through 182-N. In another
embodiment, the streaming and recommendation function 182-1 stores
the song recommendations in corresponding data structures
maintained for the users identified as friends of the user 172-1.
For example, if the user 172-2 is identified as a friend of the
user 172-1, the song recommendation may be stored in a list of
received song recommendations maintained for the user 172-2 in, for
example, the user account of the user 172-2. This list of received
song recommendations may thereafter be processed by the streaming
and recommendation function 182-2 associated with the user
172-2.
[0079] In this example, while streaming the song to the user device
170-1 of the user 172-1, the streaming and recommendation function
182-1 receives one or more song recommendations from one or more
other users identified as friends of the user 172-1 (step 606).
More specifically, song recommendations are automatically sent to
the user 172-1 in response to playback of corresponding songs by
the users identified as friends of the user 172-1. Again, the song
recommendations may be provided directly to the streaming and
recommendation function 182-1 or stored in a data structure
associated with the user 172-1. After receiving the song
recommendations, the streaming and recommendation function 182-1
may optionally filter the song recommendations based on, for
example, user, genre, artist, title, album, lyrics, date of
release, or the like (step 608).
[0080] Based on the user preferences of the user 172-1, the
streaming and recommendation function 182-1 then automatically
selects a next song to play from a group of songs including the
songs identified by the song recommendations received in step 606,
or the song recommendations that were not filtered or removed if
the filtering step 608 is performed (step 610). The group of songs
may be only the songs identified by the song recommendations
received in step 606 or the song recommendations resulting from the
filtering step 608 if filtering is performed. In another
embodiment, the group of songs includes the songs identified by the
song recommendations received in step 606 or resulting from the
filtering step 608 and one or more of the following: one or more
songs identified by previous song recommendations sent to the user
172-1, one or more songs identified by the user 172-1, one or more
songs selected or recommended by the media service 176, or the
like. Further, in the preferred embodiment, the group of songs is
maintained as a list of songs such as, for example, a play list.
Note that if previous song recommendations are considered, previous
song recommendations may expire, and therefore no longer be
considered, after a defined amount of time has lapsed since the
song recommendations were received.
[0081] As discussed above, the user preferences used to select the
next song to play may include a weight or priority assigned to each
of a number of categories such as user, genre, decade of release,
and availability. Generally, in this embodiment, availability
identifies whether the user 172-1 has access rights to the
corresponding song. For example, availability may refer to whether
songs are available to the user 176-1 for free or for some fee
(e.g., purchase fee, subscription fee, or the like).
[0082] In the preferred embodiment, the next song to play is
selected by first scoring the songs in the group of songs
associated with the user 172-1 based on the user preferences of the
user 172-1 and then selecting the song having the highest or most
preferred score as the next song to play. Once the next song to
play is selected, the streaming media service 176 obtains the next
song from the music repository 180 (step 612). At this point, the
process returns to step 602 such that the streaming and
recommendation function 182-1 begins streaming the next song to the
user device 170-1 of the user 172-1. Steps 602 through 612 are
repeated until the playback session is terminated.
[0083] FIG. 19 is a more detailed flow chart illustrating the
operation of the streaming and recommendation function 182-1
according to an exemplary embodiment of the present disclosure.
First, a playlist for the user 172-1 is initialized (step 700). In
this embodiment, the playlist may be initialized with one or more
songs selected by the user 172-1, one or more songs selected or
recommended by the streaming media service 176, one or more songs
previously recommended to the user 172-1 by other users identified
as friends of the user 172-1, or the like. Further, in this
exemplary embodiment, the songs in the playlist are scored based on
the user preferences of the user 172-1, and the playlist is sorted
based on the scores of the songs. Note that in an alternative
embodiment, the playlist may be initialized as an empty
playlist.
[0084] Next, assuming that the playlist is not initialized to an
empty playlist, the streaming and recommendation function 182-1
begins streaming a select song from the playlist to the user device
170-1 of the user 172-1 for playback (step 702). In this exemplary
embodiment, the select song may be a first song in the playlist,
which is the song having the highest or most preferred score. The
streaming and recommendation function 182-1 then determines whether
it is time to select a next song to stream to the user device 170-1
of the user 172-1 for playback (step 704). A determination that it
is time to select the next song to stream to the user device 170-1
may be made when, for example, a threshold amount of the current
song has been streamed to and/or played by the user device 170-1 or
when the user 172-1 chooses to skip to the next song.
[0085] If a determination is made that it is not time to select the
next song, the streaming and recommendation function 182-1 then
determines whether a song recommendation has been received on
behalf of the user 172-1 (step 706). Note that while receipt and
processing of a single song recommendation is discussed, multiple
song recommendations may be received and processed at this time.
Again, the song recommendations provided to the user 172-1 from
other users identified as friends of the user 172-1 may be sent
directly to the streaming and recommendation function 182-1 or
stored in a data structure associated with the user 172-1 such as,
for example, the user account of the user 172-1. If a song
recommendation has not been received, then the process returns to
step 702 such that the current song is continued to be streamed to
the user device 170-1 of the user 172-1 and the process is
repeated.
[0086] If a song recommendation has been received, then the
streaming and recommendation function 182-1 optionally filters the
song recommendation based on one or more filtering criteria such
as, for example, artist, genre, date or decade of release,
recommending user, or the like (step 708). If the song
recommendation is to be filtered, then the streaming and
recommendation function 182-1 disregards or discards the song
recommendation (step 710), and the process then returns to step 702
and is repeated. If the song recommendation is not to be filtered,
then the streaming and recommendation function 182-1 scores the
song identified by the song recommendation based on the user
preferences of the user 172-1 (step 712). The song recommendation
function then updates the playlist of the user 172-1 to include an
entry for the song identified by the song recommendation (step
714). When updating the playlist, the song identified by the song
recommendation may be inserted into the playlist at a position
determined based on the score of the song such that the playlist
remains sorted based on the scores of the media items in the
playlist. Alternatively, the song identified by the song
recommendation may be inserted at any arbitrary location within the
playlist. The playlist may then be sorted based on score. At this
point, the process returns to step 702 and streaming of the current
song is continued.
[0087] Note that if the user 172-1 does not have access rights to
the song identified by the song recommendation that was added to
the playlist, access rights to the song may be automatically
obtained for the user 172-1 by, for example, charging a
corresponding fee to an account of the user 172-1. Alternatively,
if the user 172-1 does not have access rights, a preview of the
song, rather than the song, may be added to the playlist.
[0088] Returning to step 704, once a determination is made that it
is time to select the next song to be streamed to and played by the
user device 170-1 of the user 172-1, the streaming and
recommendation function 182-1 sends a song recommendation
identifying the song to one or more other users identified as
friends of the user 172-1 (step 716). Then, a no-repeat-factor
(NRF) is applied to the song in order to decrease the score of the
song as discussed above (step 718). The playlist is then updated
(step 720). More specifically, in this embodiment, the
no-repeat-factor and thus the scores of songs previously played are
updated. The playlist is then resorted based on the updated scores
of the song being played or just completed as well as the updated
scores of songs previously played. The streaming and recommendation
function 182-1 then automatically selects a song from the playlist
having the highest or most preferential score as the next song to
play (step 722). The process then returns to step 702 such that
streaming of the next song begins, and the process is repeated.
[0089] FIG. 20 is a block diagram of the central server 168 of FIG.
17 according to one embodiment of the present disclosure. In
general, the central server 168 includes a control system 186
having associated memory 188. In this example, the streaming media
service 176 is implemented in software and stored in the memory
188. However, the present disclosure is not limited thereto. The
streaming media service 176 may be implemented in software,
hardware, or a combination thereof. The central server 168 also
includes one or more storage units 190 such as, for example, one or
more hard disk drives. In one embodiment, the user account
repository 178 and the music repository 180 are stored in the one
or more storage units 190. However, the present disclosure is not
limited thereto. The central server 168 also includes a
communication interface 192 communicatively coupling the central
server 168 to the network 174 (FIG. 17). Lastly, the central server
168 may include a user interface 194, which may include components
such as, for example, a display, one or more user input devices, or
the like.
[0090] FIG. 21 is a block diagram of the user device 170-1 of FIG.
17 according to one embodiment of the present disclosure. This
discussion is equally applicable to the other user devices 170-2
through 170-N. In general, the user device 170-1 includes a control
system 196 having associated memory 198. In this example, the
streaming client 184-1 is implemented in software and stored in the
memory 198. However, the present disclosure is not limited thereto.
The streaming media client 184-1 may be implemented in software,
hardware, or a combination thereof. The user device 170-1 also
includes a communication interface 200 communicatively coupling the
user device 170-1 to the network 174 (FIG. 17). Lastly, the user
device 170-1 includes a user interface 202, which may include
components such as, for example, a display, one or more speakers,
one or more user input devices, or the like.
[0091] The present disclosure provides substantial opportunity for
variation without departing from the spirit or scope of the present
disclosure. For example, while FIG. 1 illustrates the peer devices
12-16 forming the P2P network via local wireless communication and
FIG. 4 illustrates the peer devices 12'-16' forming the P2P network
via the network 20, the present disclosure is not limited to either
a local wireless P2P network or a WAN P2P network in the
alternative. More specifically, a particular peer device, such as
the peer device 12, may form a P2P network with other peer devices
using both local wireless communication and the network 20. Thus,
for example, the peer device 12 may receive recommendations from
both the peer devices 14, 16 (FIG. 1) via local wireless
communication and from the peer devices 14'-16' (FIG. 4) via the
network 20.
[0092] As another example, while the discussion herein focuses on
song recommendations, the present disclosure is not limited
thereto. The present disclosure is equally applicable to
recommendations for other types of media presentations such as, for
example, other types of audio presentations such as podcasts, audio
books, or audio programs; video presentations such as movies,
television programs, or user-generated video clips; or the like.
Thus, the present disclosure may additionally or alternatively
provide movie recommendations, television program recommendations,
or the like.
[0093] Those skilled in the art will recognize improvements and
modifications to the preferred embodiments of the present
disclosure. All such improvements and modifications are considered
within the scope of the concepts disclosed herein and the claims
that follow.
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