U.S. patent application number 15/786165 was filed with the patent office on 2018-02-08 for composite task processor.
This patent application is currently assigned to EMPIRE TECHNOLOGY DEVELOPMENT LLC. The applicant listed for this patent is EMPIRE TECHNOLOGY DEVELOPMENT LLC. Invention is credited to Jun Fang.
Application Number | 20180039522 15/786165 |
Document ID | / |
Family ID | 54391934 |
Filed Date | 2018-02-08 |
United States Patent
Application |
20180039522 |
Kind Code |
A1 |
Fang; Jun |
February 8, 2018 |
COMPOSITE TASK PROCESSOR
Abstract
Technologies are generally described for systems, devices and
methods effective to process a composite task to be applied to an
ontology. In some examples, the methods may include a processor
receiving a composite task. The methods may include the processor
transforming the composite task into a set of atomic tasks. The set
of atomic tasks may include at least a first atomic task, a second
atomic task, and a third atomic task. The methods may include the
processor determining that the first atomic task is equivalent to
the second atomic task based on the ontology. The methods may
include the processor removing the second atomic task from the set
of atomic tasks to generate a list of atomic tasks. The methods may
include the processor applying the list of atomic tasks to the
ontology.
Inventors: |
Fang; Jun; (Xi'an,
CN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
EMPIRE TECHNOLOGY DEVELOPMENT LLC |
Wilmington |
DE |
US |
|
|
Assignee: |
EMPIRE TECHNOLOGY DEVELOPMENT
LLC
Wilmington
DE
|
Family ID: |
54391934 |
Appl. No.: |
15/786165 |
Filed: |
October 17, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14647701 |
May 27, 2015 |
9811383 |
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PCT/CN2014/076770 |
May 5, 2014 |
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15786165 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 9/52 20130101; G06F
9/5038 20130101 |
International
Class: |
G06F 9/50 20060101
G06F009/50; G06F 9/52 20060101 G06F009/52 |
Claims
1. A method to execute a composite task, the method comprising, by
one or more processors: obtaining the composite task; transforming
the composite task into a plurality of atomic tasks; determining,
based on a semantic relation graph, respective semantic
relationships between the plurality of atomic tasks; generating,
based on the respective semantic relationships, from the plurality
of atomic tasks, a list of atomic tasks, wherein generating the
list of atomic tasks includes generating a list inclusive of atomic
tasks that are semantically different from each other in the
semantic relation graph; ordering the atomic tasks, included in the
list of atomic tasks, to generate an ordered list of atomic tasks,
wherein ordering the atomic tasks is based on respective semantic
relationships between the atomic tasks included in the list of
atomic tasks; and processing at least a first selected atomic task
in the ordered list of atomic tasks to execute the composite task,
wherein the first selected atomic task is less semantically
restrictive than at least one of the atomic tasks in the ordered
list of atomic tasks, and wherein the first selected atomic task is
more semantically restrictive than at least another one of the
atomic tasks in the ordered list of atomic tasks.
2. The method of claim 1, wherein generating the list of atomic
tasks includes removing, from the plurality of atomic tasks, all
except one atomic task, which are semantically equivalent to each
other in the semantic relation graph.
3. The method of claim 1, further comprising: constructing the
semantic relation graph, prior to obtaining the composite task.
4. The method of claim 3, wherein constructing the semantic
relation graph includes constructing the semantic relation graph
based on an ontology.
5. The method of claim 1, further comprising, prior to obtaining
the composite task: obtaining a first symbol and a second symbol in
an ontology; determining a semantic relationship between the first
symbol and the second symbol; and generating, based at least on the
semantic relationship between the first symbol and the second
symbol, the semantic relation graph, wherein: determining the
respective semantic relationships between the plurality of atomic
tasks includes determining, based on the semantic relation graph,
that a particular atomic task, of the plurality of atomic tasks, is
equivalent to another atomic task, of the plurality of atomic
tasks, and generating the list of atomic tasks includes removing
one of the particular atomic task and the another atomic task from
the plurality of atomic tasks.
6. The method of claim 1, further comprising: obtaining a response
to the processing of the first selected atomic task; and
determining, based on the response, not to process the at least
another one of the atomic tasks that is less semantically
restrictive than the first selected atomic task.
7. The method of claim 1, wherein transforming the composite task
into the plurality of atomic tasks includes: transforming the
composite task into a standard form descriptive logic notation,
wherein the standard form descriptive logic notation of the
composite task includes inclusion axioms, assertions, queries, and
composite task concepts; transforming the inclusion axioms into
additional concepts; transforming the composite task concepts and
the additional concepts into negation normal form concepts; and
transforming the negation normal form concepts into
conjunctions.
8. A method to execute a composite task, the method comprising, by
one or more processors: obtaining the composite task; transforming
the composite task into a plurality of atomic tasks; determining,
based on a semantic relation graph, respective semantic
relationships between the plurality of atomic tasks; generating,
based on the respective semantic relationships, a list of atomic
tasks, wherein generating the list of atomic tasks includes
removing, from the plurality of atomic tasks, at least one atomic
task that is semantically equivalent, in the semantic relation
graph, to another atomic task included in plurality of atomic
tasks; ordering atomic tasks included in the list of atomic tasks
to generate an ordered list of atomic tasks, wherein ordering the
atomic tasks is based on respective semantic relationships between
the atomic tasks included in the list of atomic tasks; processing
at least a first selected atomic task in the ordered list of atomic
tasks to execute the composite task; obtaining a response to the
processing of the first selected atomic task; and determining,
based on the response, not to process another atomic task, in the
ordered list of atomic tasks, to execute the composite task,
wherein the first selected atomic task is more semantically
restrictive, in the semantic relationship graph, than the another
atomic task in the ordered list of atomic tasks.
9. The method of claim 8, further comprising, prior to obtaining
the composite task, generating the semantic relation graph by:
obtaining a first symbol and a second symbol in an ontology; and
determining a semantic relationship between the first symbol and
the second symbol in the ontology.
10. The method of claim 8, wherein processing at least the first
selected atomic task includes selecting an atomic task that is less
semantically restrictive than at least one of the atomic tasks in
the ordered list of atomic tasks.
11. The method of claim 8, wherein: the plurality of atomic tasks
includes a first atomic task, a second atomic task, a third atomic
task, and a fourth atomic task, and removing, from the plurality of
atomic tasks, the at least the atomic task includes removing the
second atomic task and the fourth atomic task that are semantically
equivalent, in the semantic relation graph, to the first atomic
task and the third atomic task respectively.
12. The method of claim 8, wherein transforming the composite task
into the plurality of atomic tasks includes: transforming the
composite task into a standard form descriptive logic notation,
wherein the standard form descriptive logic notation of the
composite task includes inclusion axioms, assertions, queries, and
composite task concepts; transforming the inclusion axioms into
additional concepts; transforming the composite task concepts and
the additional concepts into negation normal form concepts; and
transforming the negation normal form concepts into
conjunctions.
13. The method of claim 8, further comprising: constructing the
semantic relation graph based on an ontology, wherein the semantic
relation graph illustrates relationships between standard form
descriptive logic notations and symbols of the ontology.
14. A device configured to execute a composite task, the device
comprising: one or more processors; and a memory, operably coupled
to the one or more processors, configured to store instructions,
which in response to execution by the one or more processors, cause
the one or more processors to: obtain the composite task; transform
the composite task into a plurality of atomic tasks; determine,
based on a semantic relation graph, respective semantic
relationships between the plurality of atomic tasks; generate,
based on the respective semantic relationships, a list of atomic
tasks, wherein the list of atomic tasks includes atomic tasks that
are semantically different from each other in the semantic relation
graph; order the atomic tasks included in the list of atomic tasks
to generate an ordered list of atomic tasks, wherein ordering the
atomic tasks is based on respective semantic relationships between
the atomic tasks included in the list of atomic tasks; and process
at least a first selected atomic task in the ordered list of atomic
tasks to execute the composite task, wherein the first selected
atomic task is less semantically restrictive than at least one of
the atomic tasks in the ordered list of atomic tasks, and wherein
the first selected atomic task is more semantically restrictive
than at least another one of the atomic tasks in the ordered list
of atomic tasks.
15. The device of claim 14, wherein, prior to obtaining the
composite task, the instructions, in response to execution by the
one or more processors, further cause the one or more processors
to: obtain a first symbol and a second symbol in an ontology;
determine a semantic relationship between the first symbol and the
second symbol; and generate, based at least on the semantic
relationship between the first symbol and the second symbol, the
semantic relation graph.
16. The device of claim 14, wherein, to transform the composite
task into the plurality of atomic tasks, the instructions, in
response to execution by the one or more processors, cause the one
or more processors to: transform the composite task into a standard
form descriptive logic notation, wherein the standard form
descriptive logic notation of the composite task includes inclusion
axioms, assertions, queries, and composite task concepts; transform
the inclusion axioms and into additional concepts; transform the
composite task concepts and the additional concepts into negation
normal form concepts; and transform the negation normal form
concepts into conjunctions.
17. The device of claim 14, wherein the instructions, in response
to execution by the one or more processors, further cause the one
or more processors to: obtain a response to the processing of the
first selected atomic task; and determine, based on the response,
not to process the at least another one of the atomic tasks that is
less semantically restrictive than the first selected atomic
task.
18. The device of claim 14, wherein the memory is further operable
to store the semantic relation graph.
19. The device of claim 14, wherein the instructions, in response
to execution by the one or more processors, further cause the one
or more processors to: access the semantic relation graph over a
network.
20. The device of claim 14, wherein the instructions, in response
to execution by the one or more processors, further cause the one
or more processors to: generate, based on an ontology stored in the
memory, the semantic relation graph, wherein the semantic relation
graph illustrates that: a first symbol of the ontology is
semantically equivalent to a second symbol of the ontology, a third
symbol of the ontology is semantically more restrictive than the
second symbol of the ontology, and the third symbol of the ontology
is semantically less restrictive than a fourth symbol of the
ontology.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This Application is a continuation application under 35
U.S.C. .sctn. 120 of U.S. patent application Ser. No. 14/647,701,
filed on May 27, 2015, which is a U.S. National Stage filing under
35 U.S.C. .sctn. 371 of International Application No.
PCT/CN2014/076770, filed on May 5, 2014. The disclosures of U.S.
patent application Ser. No. 14/647,701 and International
Application No. PCT/CN2014/076770 are hereby incorporated herein by
reference in their entireties.
BACKGROUND
[0002] Unless otherwise indicated herein, the materials described
in this section are not prior art to the claims in this application
and are not admitted to be prior art by inclusion in this
section.
[0003] In a parallel processing arrangement, more than one central
processing unit (CPU) or processor core may execute a program or
multi computational threads. A parallel processing arrangement may
execute instructions faster than serial processing. The program may
be divided in such a way that separate CPUs or cores can execute
different portions of the program without interfering with each
other.
SUMMARY
[0004] In an example, methods effective to process a composite task
to be applied to an ontology are described. The methods may include
a processor receiving the composite task. The methods may include
the processor transforming the composite task into a set of atomic
tasks. The set of atomic tasks may include at least a first atomic
task, a second atomic task, and a third atomic task. The methods
may include the processor determining that the first atomic task is
equivalent to the second atomic task based on the ontology. The
methods may include the processor removing the second atomic task
from the set of atomic tasks to generate a list of atomic tasks.
The methods may include the processor applying the list of atomic
tasks to the ontology.
[0005] In an example, methods effective to process a composite task
to be applied to an ontology are described. The methods may include
a processor receiving the composite task. The methods may include
the processor transforming the composite task into a set of atomic
tasks. The set of atomic tasks may include at least a first atomic
task, a second atomic task, and a third atomic task. The methods
may include the processor analyzing a semantic relationship between
the first atomic task, the second atomic task and the third atomic
task based on a semantic relation graph. The semantic relation
graph may be based on the ontology. The methods may include the
processor determining a first semantic relationship between the
first atomic task and the second atomic task. The first atomic task
may be more semantically restrictive than the second atomic task.
The methods may include the processor determining a second semantic
relationship between the second atomic task and the third atomic
task. The second atomic task may be more semantically restrictive
than the third atomic task. The methods may include the processor
generating an ordered list of the first atomic task, the second
atomic task and the third atomic task based on the determined first
and second semantic relationships.
[0006] In an example, devices configured to process a composite
task to be applied to an ontology are described. The devices may
include a processor and a memory. The memory may include the
ontology, a semantic relation graph, and instructions. The
instructions, when executed by the processor, may cause the
processor to receive the composite task. The instructions, when
executed by the processor, may cause the processor to transform the
composite task into a set of atomic tasks. The set of atomic tasks
may include at least a first atomic task, a second atomic task, and
a third atomic task. The instructions, when executed by the
processor, may cause the processor to determine the first atomic
task is equivalent to the second atomic task based on the semantic
relation graph. The instructions, when executed by the processor,
may cause the processor to remove the second atomic task from the
set of atomic tasks to generate a list of atomic tasks. The
instructions, when executed by the processor, may cause the
processor to order the list of atomic tasks based on the semantic
relation graph. The instructions, when executed by the processor,
may cause the processor to apply the ordered list of atomic tasks
to the ontology.
[0007] The foregoing summary is illustrative only and is not
intended to be in any way limiting. In addition to the illustrative
aspects, embodiments, and features described above, further
aspects, embodiments, and features will become apparent by
reference to the drawings and the following detailed
description.
BRIEF DESCRIPTION OF THE FIGURES
[0008] FIG. 1 illustrates an example composite task processor
system;
[0009] FIG. 2 illustrates the example composite task processor
system of FIG. 1 with additional details relating to atomic
tasks;
[0010] FIG. 3 depicts a flow diagram for example processes to
process composite tasks;
[0011] FIG. 4 illustrates computer program products configured to
process composite tasks; and
[0012] FIG. 5 is a block diagram illustrating an example computing
device that is arranged to process composite tasks, all arranged in
accordance with at least some embodiments described herein.
DETAILED DESCRIPTION
[0013] In the following detailed description, reference is made to
the accompanying drawings, which form a part hereof. In the
drawings, similar symbols typically identify similar components,
unless context dictates otherwise. The illustrative embodiments
described in the detailed description, drawings, and claims are not
meant to be limiting. Other embodiments may be utilized, and other
changes may be made, without departing from the spirit or scope of
the subject matter presented herein. It will be readily understood
that the aspects of the present disclosure, as generally described
herein, and illustrated in the Figures, can be arranged,
substituted, combined, separated, and designed in a wide variety of
different configurations, all of which are explicitly contemplated
herein.
[0014] This disclosure is generally drawn, inter alia, to methods,
apparatus, systems, devices, and computer program products related
to a composite task processor.
[0015] Briefly stated, technologies are generally described for
systems, devices and methods effective to process a composite task
to be applied to an ontology. The ontology may include nodes
representing concepts, and links between the nodes representing
relationships among the concepts. The methods may include a
processor receiving a composite task. For example, a composite task
may include multiple tasks for the processor to apply to the
ontology. In an example, the ontology may relate to mathematics (or
math) and the composite task may be a request to find the area of a
complicated shape. The methods may include the processor
transforming the composite task into a set of atomic tasks such as
tasks to find the area of simpler shapes like circles. For example,
the composite task may include multiple smaller tasks or atomic
tasks to be applied to the ontology. The set of atomic tasks may
include at least a first atomic task, a second atomic task, and a
third atomic task. The methods may include the processor
determining that the first atomic task is equivalent to the second
atomic task based on the ontology. For example, the ontology may be
a math ontology. The first atomic task and the second atomic task
may both relate to determining the area of a circle. Based on a
math ontology, the first and second atomic tasks may be determined
to the equivalent. The methods may include the processor removing
the second atomic task from the set of atomic tasks to generate a
list of atomic tasks. For example, if the first atomic task is
equivalent to the second atomic task, then only one of the atomic
tasks may need to be applied to the ontology to process the
composite task. The methods may include the processor applying the
list of atomic tasks to the ontology.
[0016] FIG. 1 illustrates an example composite task processor
system, arranged in accordance with at least some embodiments
described herein. As discussed in more detail below, in some
examples, a system 100 may include a processor 104 and a memory
106. Processor 104 may be configured to be in communication with
memory 106. Memory 106 may include an ontology 130, a semantic
relation graph 140, transformation instructions 108, equivalence
instructions 110, implication list instructions 112, and binary
reasoning instructions 114. Processor 104 may also be configured to
be in communication with ontology 130 and semantic relation graph
140 over a network 136 if ontology 130 and semantic relation graph
140 are not stored in memory 106. As discussed in more detail
below, processor 104 may process composite task 102 and apply
composite task 102 to ontology 130.
[0017] In one example, processor 104 may receive one or more
composite tasks 102. Composite task 102 may include multiple
reasoning requests or atomic tasks to be applied to ontology 130 by
processor 104. Processor 104 may process composite task 102 by
executing transformation instructions 108 to transform composite
task 102 into a set of atomic tasks 126. Atomic tasks in set of
atomic tasks 126 may be subset tasks of composite task 102 where
each atomic task in set of atomic tasks 126 may be a task that may
be difficult to further divide into smaller tasks. For example, if
composite task 102 is "take care of dog", atomic tasks in set of
atomic tasks 126 may include; "feed dog", "give dog water", "walk
dog", "clean up after dog", "groom dog", etc. Processor 104 may
transform composite task 102 into set of atomic tasks 126 such that
atomic tasks in set of atomic tasks 126 are in standard form
descriptive logic notations and symbols--explained in more detail
below.
[0018] Processor 104 may execute equivalence instructions 110 on
atomic tasks in set of atomic tasks 126. In executing equivalence
instructions 110, processor 104 may utilize semantic relation graph
140 to determine atomic tasks in set of atomic tasks 126 which are
semantically equivalent within semantic relation graph 140. For
example, the atomic tasks "feed the dog" and "give the dog dinner"
may be semantically equivalent in semantic relation graph 140 and
in ontology 130. Semantic relation graph 140 may be constructed
prior to processor 104 receiving composite task 102, may be
generated based on ontology 130 and may illustrate relationships
between standard form descriptive logic notations and symbols in
ontology 130--explained in more detail below. Semantic relation
graph 140 may reflect semantic relationships between the atomic
tasks in set of atomic tasks 126.
[0019] Processor 104 may generate a list of atomic tasks 128 from
set of atomic tasks 126 by removing all but one of each atomic task
in set of atomic tasks 126 determined to be equivalent. For
example, if atomic task A and atomic task B are determined to be
equivalent, processor 104 may remove all instances of atomic task A
and atomic task B from set of atomic tasks 126, except for one
instance of atomic task A of atomic task B, to generate list of
atomic tasks 128.
[0020] Processor may execute implication list instructions 112 on
list of atomic tasks 128. In executing implication list
instructions 112, processor 104 may utilize semantic relation graph
140 to order list of atomic tasks 128 and generate ordered list of
atomic tasks 132. Ordered list of atomic tasks 132 may include
atomic tasks that are related within semantic relation graph 140
such as one atomic task implying or being more semantically
restrictive than another, related atomic task. For example, if an
individual can legally drive a car, than this may imply that the
individual has a license; and having a license may imply that the
individual is over sixteen years old. In the previous example,
ordered list of atomic tasks 132 may include: can legally drive a
car.fwdarw.has a license.fwdarw.over sixteen years old.
[0021] Processor 104 may execute binary reasoning instructions 114
on ordered list of atomic tasks 132 to determine atomic tasks to
apply to ontology 130. For example, if the more semantically
restrictive task "take care of dog" can be processed, then
processor 104 need not thereafter process the less semantically
restrictive task "feed the dog." Processor 104, executing binary
reasoning instructions 114, may select an atomic task from
approximately the middle of ordered list of atomic tasks 132 to
apply to ontology 130. For example, if there are n atomic tasks in
ordered list of atomic tasks 132, processor 104 may select atomic
task at position n/2 within ordered list of atomic tasks 132 where
n/2 is an integer. If n/2 is not an integer, processor 104 may
select atomic task at position (n+1)/2. Processor 104 may receive a
response to applying the selected atomic task to ontology 130. A
response from applying the selected atomic task to ontology 130 may
indicate whether processor 104 can execute the selected atomic task
and less semantically restrictive tasks. Based on the response and
binary reasoning instructions 114, processor 104 may select a
second atomic task from ordered list of atomic tasks 132 to apply
to ontology 130. Processor 104 executing binary reasoning
instructions 114 and applying atomic tasks from ordered list of
atomic tasks 132 to ontology 130, may determine which atomic tasks
within ordered list of atomic tasks 132 must be executed and
applied to ontology 130 to execute composite task 102. For example,
if composite task 102 is to determine habits of drivers with low
insurance rates, and binary reasoning instructions are executed on
ordered list of atomic tasks 132 (can legally drive a
car.fwdarw.has a license.fwdarw.over sixteen years old), then
processor 104 may only apply the atomic task of determining whether
an individual "can legally drive a car" to ontology 130. A response
to this atomic task may indicate that ontology 130 may be able to
determine an individual can legally drive a car. As a consequence,
the atomic tasks of determining an individual "has a license" and
determining an individual is "over sixteen years of age" may not be
applied to ontology 130 as these two atomic tasks are implied by
the first atomic task of determining an individual "can legally
drive a car." Processor 104 may apply atomic tasks from ordered
list of atomic tasks 132 with use of binary reasoning instructions
114 to ontology 130 to execute composite task 102. Use of binary
reasoning instructions 114 may result in less processing time, less
processing memory, and less power than applying all atomic tasks in
ordered list of atomic tasks 132 on ontology 130.
[0022] FIG. 2 illustrates example composite task processor system
100 of FIG. 1 with additional details relating to atomic tasks,
arranged in accordance with at least some embodiments described
herein. FIG. 2 is substantially similar to FIG. 1, with additional
details. Those components in FIG. 2 that are labeled identically to
components of FIG. 1 will not be described again for the purposes
of clarity.
[0023] In one example, processor 104 may receive composite task
102. Composite task 102 may include multiple reasoning requests or
atomic tasks to be applied to ontology 130 by processor 104.
Processor 104 may process composite task 102 by executing
transformation instructions 108 to transform composite task 102
into set of atomic tasks 126, including atomic task 216, atomic
task 218, atomic task 220, atomic task 222, and atomic task
224.
[0024] Ontology 130 may include standard form descriptive logic
notations that may be used to model concepts, roles, and
individuals, and the relationships therebetween. Ontology 130 may
include axioms in descriptive logic notation relating concepts
and/or roles within ontology 130. Axioms within ontology 130 may
denote semantic data or knowledge and links between axioms may
denote relationships among axioms. Ontology 130, may be looked at
as an axiom set, and may be used to denote a semantic data set or a
knowledge base. Ontology 130 may include descriptive logic notation
that may include the standard logic notation of the Semantic
Web.
[0025] Processor 104, executing transformation instructions 108,
may transform composite task 102 into standard form descriptive
logic notations. Composite task 102, transformed into standard form
descriptive logic notation may include inclusion axioms.
Transformation instructions 108 may include instructions to
transform inclusion axioms in composite task 102 into concepts.
Transformation instructions 108 may include instructions to
subsequently transform concepts in composite task 102, including
concepts derived from transforming inclusion axioms in composite
task 102, into a negation normal form. Transformation instructions
108 may include a negation normal form of a concept, for example,
when negation occurs only in front of a concept name.
Transformation instructions 108 may include instructions to
subsequently transform the negation normal form concepts into a
conjunction form. Transformation instructions 108 may include
instructions to separate concepts or assertions connected with the
conjunctions into different atomic tasks.
[0026] Processor 104 may further execute transformation
instructions 108 to transform queries in composite task 102 into
assertions. For example, a query in composite task 102 may be
transformed into multiple assertions. Processor 104, executing
transformation instructions 108, may separate the assertions
transformed from queries in composite task 102 into atomic tasks to
be applied to ontology 130. Processor 104 may transform inclusion
axioms, concepts, assertions, and queries in composite task 102
into set of atomic tasks 126.
[0027] Semantic relation graph 140 may be constructed prior to
processor 104 receiving composite task 102 and may be generated
based on ontology 130. Semantic relation graph 140, based on
ontology 130, may illustrate relationships between standard form
descriptive logic notations and symbols in ontology 130. Semantic
relation graph 140 may be generated by processor 104 and stored in
memory 106. Processor 104 may be configured to be in communication
with semantic relation graph 140 over a network 136 if semantic
relation graph 140 was not generated by processor 104 and/or is not
stored in memory 106. Semantic relation graph 140 may include
semantic relationships between symbols of ontology 130. Semantic
relationships in semantic relation graph 140 may include semantic
relations between pairs of symbols. For example, a first and a
second symbol may be related in semantic relations graph 140 as
equivalent, the first symbol may be more semantically restrictive
than the second symbol, or the second symbol may be more
semantically restrictive than the first symbol. Semantic
relationships between symbols on an ontology may be used to
determine relationships between atomic tasks in set of atomic tasks
126.
[0028] Processor 104 or another processor may construct semantic
relation graph 140 based on ontology 130. A semantic relationship
may be determined for all symbols within ontology 130. The
determined semantic relationships between all symbols of ontology
130 may be represented in semantic relation graph 140. Semantic
relation graph 140 may be constructed by determining a semantic
relationship between a first symbol and a second symbol of ontology
130, until every possible pair combination of symbols in ontology
130 is related on semantic relation graph 140. In one example,
processor 104 may check a semantic relationship between a first
symbol and a second symbol. Processor 104 may determine the first
symbol semantically equivalent to the second symbol. Processor 104
may determine the first symbol more semantically restrictive than
the second symbol. Processor 104 may determine the second symbol
more semantically restrictive than the first symbol. Processor 104
may graph the first and second symbols on semantic relation graph
140 with the determined semantic relationship. Processor 104 may
continue to determine semantic relationships between pairs of
symbols of ontology 130 until all pair combinations have been
graphed on semantic relation graph 140. Processor 104 may construct
semantic relation graph 140 prior to receiving composite task
102.
[0029] An example construction of a semantic relation graph 140
("SG") based on ontology 130 represented by O and first and second
symbols represented by s.sub.i and s.sub.j is presented below.
TABLE-US-00001 Input: an ontology O; Output: a graph SG; 1: for
each pair (s.sub.i and s.sub.j) where s.sub.i, s.sub.j .di-elect
cons. O 2: check semantic relation between s.sub.i,s.sub.j using
the definition below 3: if s.sub.i = s.sub.j then 4: build s.sub.i
s.sub.j into graph SG 5: else if s.sub.i >> s.sub.j then 6:
build si .fwdarw.j into graph SG 7: if s.sub.i << .sub.sj
then 8: build s.sub.i .rarw. s.sub.j into SG
[0030] Reasoning for composite task 102 may be determined by the
semantic interpretation of symbols within composite task 102. A
semantic interpretation for a symbol in ontology 130 may be
determined by a syntactic definition of the symbol. Semantic
relationships between symbols within ontology 130 may be based on
the symbols syntactic definitions.
TABLE-US-00002 Definition: Given ontology O, s.sub.1 and s.sub.2
are two symbols in ontology O Let A(s) denote all axioms which
contain s in ontology O A(s).sup.s.fwdarw.s' represents replacing
symbols s with s' for all axioms A(s) 1. If
A(s.sub.1).sup.s1.fwdarw.s2 = A(s.sub.2), then s.sub.1 and s.sub.2
are semantically equivalent, denoted by s.sub.1 == s.sub.2. 2. If
A(s.sub.1).sup.s1.fwdarw.s2 A(s.sub.2), then s.sub.1 is more
semantically restricted than s.sub.2, denoted by s.sub.1 <<
s.sub.2. 3. If A(s.sub.1).sup.s1.fwdarw.s2 .OR right. A(s.sub.2),
then s.sub.2 is more semantically restricted than s.sub.1, denoted
by s.sub.1 >> s.sub.2.
This definition of the semantic relationships between two symbols
of ontology 130 may be used to construct semantic relation graph
140.
[0031] Processor 104 may execute equivalence instructions 110 on
atomic tasks 216, 218, 220, 222, and 224. For example, processor
104 may utilize semantic relation graph 140 to determine those of
atomic tasks 216, 218, 220, 222, 224 which are semantically
equivalent within semantic relation graph 140. Semantic relation
graph 140 may include semantic relationships among atomic tasks
216, 218, 220, 222, 224. In an example, as shown at 230, processor
104 may, by executing equivalence instructions 110, utilize
semantic relation graph 140 to determine that atomic task 216 is
semantically equivalent to atomic task 222. Processor 104 may
generate list of atomic tasks 128 from set of atomic tasks 126 by
removing all but one of atomic tasks 216 and 222 determined to be
equivalent. Processor 104 may determine that list of atomic tasks
128 includes atomic tasks 216, 218, 220, and 224.
[0032] Processor 104 may execute implication instructions 112 on
atomic tasks 216, 218, 220, and 224 in list of atomic tasks 128 and
may utilize semantic relation graph 140 to generate ordered list of
atomic tasks 132. Ordered list of atomic tasks 132 may include
atomic tasks that imply other atomic tasks within semantic relation
graph 140. For example, processor 104 may utilize semantic relation
graph 140 to generate ordered list of atomic tasks 132--that
includes atomic tasks 216, 218, 220, and 224. Semantic relation
graph 140 may identify atomic task 216 as implying atomic task 220,
identify atomic task 220 as implying atomic task 224, and identify
atomic task 224 as implying atomic task 218. Processor 104 may
determine ordered list of atomic tasks 132 including atomic tasks
216, 218, 220, and 224 as:
216.fwdarw.220.fwdarw.224.fwdarw.218.
[0033] Processor 104 may execute binary reasoning instructions 114
on ordered list of atomic tasks 132. Processor 104 may, by
executing binary reasoning instructions 114 on ordered list of
atomic tasks 132, determine which of atomic tasks 216, 220, 224,
218 to apply to ontology 130. Processor 104, executing binary
reasoning instructions 114, may select an atomic task from
approximately the middle of an ordered list of atomic tasks 132 to
apply to ontology 130. For example, ordered list of atomic tasks
132 may include ordered atomic tasks 216, 220, 224, 218 to apply to
ontology 130. Processor 104 may execute binary reasoning
instructions 114 and apply atomic task 220 to ontology 130.
Processor 104 may receive a response to applying atomic task 220 to
ontology 130. A response from applying an atomic task to ontology
130 may indicate whether processor 104 can execute the atomic task
on ontology 130. Based on the response and binary reasoning
instructions 114, processor 104 may select a second atomic task
from ordered list of atomic tasks 132 to apply to ontology 130. For
example, the response may indicate that atomic task 220 can be
executed on ontology 130. As a consequence, processor 104 may
determine that atomic tasks 224 and 218 do not need to be applied
to ontology 130 and may select atomic task 216 as the next atomic
task to apply to ontology 130.
[0034] Among other potential benefits, a system in accordance with
the disclosure may take less time and use less processing resources
to process a composite task. The system may avoid duplicate
processing by identifying equivalent atomic tasks of a composite
task and only process the equivalent atomic tasks once, saving
processing time and other processing resources such as battery
life, energy consumption, and memory requirements. The system may
also avoid unnecessary processing by determining atomic tasks that
do not need to be applied to the ontology based on the ordered
list, thus lowing the number of atomic tasks to apply to the
ontology and reducing processing time and resources. Concurrent
reasoning tasks may be processed efficiently.
Experimental Data
[0035] Simulations were run using a descriptive logic reasoner
(PELLET) and an application programmable interface (API) for
ontology manipulation (OWLAPI) on several Lehigh University
Benchmark (LUBM) ontologies. LUBM ontologies ranged from 10.sup.5
axioms to 10.sup.6 axioms with corresponding number of reasoning
tasks from 10.sup.4 to 10.sup.6. The syntax used was SHIF(D).
TABLE-US-00003 TABLE 1 Total Size |reasoning Ontology Syntax
|Axioms| (MB) tasks| LUBM-Lite1.sub.+10K SHIF(D) 100,729 8.03
10.sup.4 LUBM-Lite10.sub.+50K 1,001,738 80.7 5 .times. 10.sup.4
LUBM-Lite50.sub.+100K 5,096,008 697.2 10.sup.6
[0036] All experiments were run on a 2.60 GHz PENTIUM-4 processor
with 4GB of physical memory and with a maximum Java heap size set
to 3072 MB for applying PELLET. First, a semantic relation graph
140 was constructed for each ontology 130. Construction of semantic
relation graph 140 may be done prior to receiving composite task to
process and may be done off line.
TABLE-US-00004 TABLE 2 Ontology Execution Time (s) Graph Size (MS)
LUBM-Lite1 747 8.78 LUBM-Lite10 3,847 90.7 LUBM-Lite50 13,276
901.2
[0037] Experimental results indicate construction time of dozens of
minutes for ontology 130 of about 10.sup.5 axioms (LUBM-Lite1) to
several hours for ontology 130 of about 5.times.10.sup.6 axioms
(LUBM-Lite50). The experimental results illustrate the construction
of semantic relation graph 140 may be completed in a reasonable
amount of time. For ontology 130, semantic relation graph 140 need
only be constructed once, and may be constructed prior to receiving
composite task 102 to process. Semantic relation graph 140 may be
loaded into memory 106. Semantic relation graph 140 may require
slightly more memory than ontology 130 from which semantic relation
graph 140 is constructed.
TABLE-US-00005 TABLE 3 Total Execution Time (s) Non-optimized
Present Method Ontology method Ordered Binary LUBM-Lite1.sub.+10K
6.2 0.6 2.1 LUBM-Lite10.sub.+50K 150.6 12.1 20.3
LUBM-Lite50.sub.+100K 2,063.5 50.6 232.5
[0038] Table 3 illustrates the experimental amount of time to
process composite task 102 for the three ontologies 130 by standard
processing of the entire composite task (Non-optimized method) and
the present method. Table 3 includes columns for amounts of time to
generate ordered lists and binary reasoning. As shown, the present
method completed composite task 102 in significantly less time. For
ontology 130 with 10.sup.5 axioms (LUBM-Litel.sub.+10K) processing
time was decreased to about half and for ontology 130 with 10.sup.6
axioms (LUBM-Lite50.sub.+100K) processing time was reduced by over
85%.
TABLE-US-00006 TABLE 4 Actual Number of Tasks Ontology
Non-optimized method Present LUBM-Lite1.sub.+10K 10,000 2,078
LUBM-Lite10.sub.+50K 50,000 7,836 LUBM-Lite50.sub.+100K 100,000
13,765
[0039] Table 4 illustrates the number of tasks applied to ontology
130 to process composite task 102. As shown, the number of tasks
applied to ontology 130 is significantly reduced by the present
method. For ontology 130 with 10.sup.5 axioms (LUBM-Lite1.sub.+10K)
the number of tasks to apply to ontology 130 was decreased by just
under 80% for ontology 130 with 10.sup.6 axioms
(LUBM-Lite50.sub.+100K) the number of tasks to apply to ontology
130 was decreased by over 86%.
[0040] FIG. 3 illustrates a flow diagram for example processes to
process composite tasks, arranged in accordance with at least some
embodiments presented herein. The process in FIG. 3 could be
implemented using, for example, system 100 discussed above. An
example process may include one or more operations, actions, or
functions as illustrated by one or more of blocks S2, S4, S6, S8
and/or S10. Although illustrated as discrete blocks, various blocks
may be divided into additional blocks, combined into fewer blocks,
or eliminated, depending on the desired implementation.
[0041] Processing may begin at block S2, "Receive the composite
task." At block S2, the processor may receive the composite task.
The composite task may include multiple reasoning requests or
atomic tasks to be applied to an ontology by the processor.
[0042] Processing may continue from block S2 to block S4,
"Transform the composite task into a set of atomic tasks, the set
of atomic tasks including at least a first atomic task, a second
atomic task, and a third atomic task." At block S4, the processor
may transform the composite task into a set of atomic tasks. The
set of atomic tasks may include at least a first atomic task, a
second atomic task, and a third atomic task. The atomic tasks in
the set of atomic tasks may be subset tasks of the composite task
which may be difficult to divide into smaller tasks. The processor
may transform the composite task into the set of atomic tasks such
that the atomic tasks in the set of atomic tasks are in standard
form descriptive logic notations and symbols.
[0043] Processing may continue from block S4 to block S6,
"Determine that the first atomic task is equivalent to the second
atomic task based on the ontology." At block S6, the processor may
determine that the first atomic task is equivalent to the second
atomic task. The determination may be based on the ontology. The
processor may utilize a semantic relationship graph to determine
atomic tasks in the set of atomic tasks which are semantically
equivalent within the semantic relation graph. The semantic
relation graph may be constructed prior to the processor receiving
the composite task. The semantic relation graph may be generated
based on the ontology and may illustrate relationships between
standard form descriptive logic notations and symbols in the
ontology. The semantic relationship graph may include semantic
relationships between atomic tasks of the ontology.
[0044] Processing may continue from block S6 to block S8, "Remove
the second atomic task from the set of atomic tasks to generate a
list of atomic tasks." At block S8, the processor may remove the
second atomic task from the set of atomic tasks to generate a list
of atomic tasks. The processor may generate the list of atomic
tasks from the set of atomic tasks by removing all but one of each
atomic task in the set of atomic tasks determined to be
equivalent.
[0045] Processing may continue from block S8 to block S10, "Apply
the list of atomic tasks to the ontology." At block S10, the
processor may apply the list of atomic tasks to the ontology. The
processor may utilize the semantic relationship graph to order the
list of atomic tasks to generate an ordered list of atomic tasks
prior to applying the list of atomic tasks to the ontology. The
ordered list of atomic tasks may include atomic tasks that are
related within the semantic relationship graph such as one atomic
task implying another atomic task. The processor may select an
atomic task from approximately the middle of the ordered list of
atomic tasks to apply to the ontology. The processor may receive a
response to applying the selected atomic task to the ontology. A
response from applying the atomic task to the ontology may indicate
whether the ontology can execute the atomic task. Based on the
response, the processor may select a second atomic task from the
ordered list of atomic tasks to apply to the ontology. The
processor may determine atomic tasks within the ordered list of
atomic tasks that should be applied to the ontology to execute the
composite task.
[0046] FIG. 4 illustrates computer program products 400 configured
to process composite tasks, arranged in accordance with at least
some embodiments presented herein. Computer program product 400 may
include a signal bearing medium 402. Signal bearing medium 402 may
include one or more instructions 404 that, when executed by, for
example, a processor, may provide the functionality described above
with respect to FIGS. 1-3. Thus, for example, referring to system
100, processor 104 may undertake one or more of the blocks shown in
FIG. 4 in response to instructions 404 conveyed to the system 100
by signal bearing medium 402.
[0047] In some implementations, signal bearing medium 402 may
encompass a computer-readable medium 406, such as, but not limited
to, a hard disk drive, a compact disc (CD), a digital video disk
(DVD), a digital tape, memory, etc. In some implementations, signal
bearing medium 402 may encompass a recordable medium 408, such as,
but not limited to, memory, read/write (R/W) CDs, R/W DVDs, etc. In
some implementations, signal bearing medium 402 may encompass a
communications medium 410, such as, but not limited to, a digital
and/or an analog communication medium (e.g., a fiber optic cable, a
waveguide, a wired communication link, a wireless communication
link, etc.). Thus, for example, computer program product 400 may be
conveyed to one or more modules of the system 100 by an RF signal
bearing medium 402, where the signal bearing medium 402 is conveyed
by a wireless communications medium 410 (e.g., a wireless
communications medium conforming with the IEEE 802.11
standard).
[0048] FIG. 5 is a block diagram illustrating an example computing
device 500 that is arranged to process composite tasks, arranged in
accordance with at least some embodiments presented herein. In a
very basic configuration 502, computing device 500 typically
includes one or more processors 504 and a system memory 506. A
memory bus 508 may be used for communicating between processor 504
and system memory 506.
[0049] Depending on the desired configuration, processor 504 may be
of any type including but not limited to a microprocessor (.mu.P),
a microcontroller (.mu.C), a digital signal processor (DSP), or any
combination thereof. Processor 504 may include one or more levels
of caching, such as a level one cache 510 and a level two cache
512, a processor core 514, and registers 516. An example processor
core 514 may include an arithmetic logic unit (ALU), a floating
point unit (FPU), a digital signal processing core (DSP core), or
any combination thereof. An example memory controller 518 may also
be used with processor 504, or in some implementations memory
controller 518 may be an internal part of processor 504.
[0050] Depending on the desired configuration, system memory 506
may be of any type including but not limited to volatile memory
(such as RAM), non-volatile memory (such as ROM, flash memory,
etc.) or any combination thereof. System memory 506 may include an
operating system 520, one or more applications 522, and program
data 524.
[0051] Application 522 may include a composite tasks processing
algorithm 526 that is arranged to perform the functions as
described herein including those described previously with respect
to FIGS. 1-4. Program data 524 may include composite tasks
processing data 528 that may be useful for processing of composite
tasks as is described herein. In some embodiments, application 522
may be arranged to operate with program data 524 on operating
system 520 such that processing of composite tasks may be provided.
This described basic configuration 502 is illustrated in FIG. 5 by
those components within the inner dashed line.
[0052] Computing device 500 may have additional features or
functionality, and additional interfaces to facilitate
communications between basic configuration 502 and any required
devices and interfaces. For example, a bus/interface controller 530
may be used to facilitate communications between basic
configuration 502 and one or more data storage devices 532 via a
storage interface bus 534. Data storage devices 532 may be
removable storage devices 536, non-removable storage devices 538,
or a combination thereof. Examples of removable storage and
non-removable storage devices include magnetic disk devices such as
flexible disk drives and hard-disk drives (HDD), optical disk
drives such as compact disk (CD) drives or digital versatile disk
(DVD) drives, solid state drives (SSD), and tape drives to name a
few. Example computer storage media may include volatile and
nonvolatile, removable and non-removable media implemented in any
method or technology for storage of information, such as computer
readable instructions, data structures, program modules, or other
data.
[0053] System memory 506, removable storage devices 536 and
non-removable storage devices 538 are examples of computer storage
media. Computer storage media includes, but is not limited to, RAM,
ROM, EEPROM, flash memory or other memory technology, CD-ROM,
digital versatile disks (DVD) or other optical storage, magnetic
cassettes, magnetic tape, magnetic disk storage or other magnetic
storage devices, or any other medium which may be used to store the
desired information and which may be accessed by computing device
500. Any such computer storage media may be part of computing
device 500.
[0054] Computing device 500 may also include an interface bus 540
for facilitating communication from various interface devices
(e.g., output devices 542, peripheral interfaces 544, and
communication devices 546 ) to basic configuration 502 via
bus/interface controller 530. Example output devices 542 include a
graphics processing unit 548 and an audio processing unit 550,
which may be configured to communicate to various external devices
such as a display or speakers via one or more A/V ports 552.
Example peripheral interfaces 544 include a serial interface
controller 554 or a parallel interface controller 556, which may be
configured to communicate with external devices such as input
devices (e.g., keyboard, mouse, pen, voice input device, touch
input device, etc.) or other peripheral devices (e.g., printer,
scanner, etc.) via one or more I/O ports 558. An example
communication device 546 includes a network controller 560, which
may be arranged to facilitate communications with one or more other
computing devices 562 over a network communication link via one or
more communication ports 564.
[0055] The network communication link may be one example of a
communication media. Communication media may typically be embodied
by computer readable instructions, data structures, program
modules, or other data in a modulated data signal, such as a
carrier wave or other transport mechanism, and may include any
information delivery media. A "modulated data signal" may be a
signal that has one or more of its characteristics set or changed
in such a manner as to encode information in the signal. By way of
example, and not limitation, communication media may include wired
media such as a wired network or direct-wired connection, and
wireless media such as acoustic, radio frequency (RF), microwave,
infrared (IR) and other wireless media. The term computer readable
media as used herein may include both storage media and
communication media.
[0056] Computing device 500 may be implemented as a portion of a
small-form factor portable (or mobile) electronic device such as a
cell phone, a personal data assistant (PDA), a personal media
player device, a wireless web-watch device, a personal headset
device, an application specific device, or a hybrid device that
include any of the above functions. Computing device 500 may also
be implemented as a personal computer including both laptop
computer and non-laptop computer configurations.
[0057] The present disclosure is not to be limited in terms of the
particular embodiments described in this application, which are
intended as illustrations of various aspects. Many modifications
and variations can be made without departing from its spirit and
scope, as will be apparent to those skilled in the art.
Functionally equivalent methods and apparatuses within the scope of
the disclosure, in addition to those enumerated herein, will be
apparent to those skilled in the art from the foregoing
descriptions. Such modifications and variations are intended to
fall within the scope of the appended claims. The present
disclosure is to be limited only by the terms of the appended
claims, along with the full scope of equivalents to which such
claims are entitled. It is to be understood that this disclosure is
not limited to particular methods, reagents, compounds compositions
or biological systems, which can, of course, vary. It is also to be
understood that the terminology used herein is for the purpose of
describing particular embodiments only, and is not intended to be
limiting.
[0058] With respect to the use of substantially any plural and/or
singular terms herein, those having skill in the art can translate
from the plural to the singular and/or from the singular to the
plural as is appropriate to the context and/or application. The
various singular/plural permutations may be expressly set forth
herein for sake of clarity.
[0059] It will be understood by those within the art that, in
general, terms used herein, and especially in the appended claims
(e.g., bodies of the appended claims) are generally intended as
"open" terms (e.g., the term "including" should be interpreted as
"including but not limited to," the term "having" should be
interpreted as "having at least," the term "includes" should be
interpreted as "includes but is not limited to," etc.). It will be
further understood by those within the art that if a specific
number of an introduced claim recitation is intended, such an
intent will be explicitly recited in the claim, and in the absence
of such recitation, no such intent is present. For example, as an
aid to understanding, the following appended claims may contain
usage of the introductory phrases "at least one" and "one or more"
to introduce claim recitations. However, the use of such phrases
should not be construed to imply that the introduction of a claim
recitation by the indefinite articles "a" or "an" limits any
particular claim containing such introduced claim recitation to
embodiments containing only one such recitation, even when the same
claim includes the introductory phrases "one or more" or "at least
one" and indefinite articles such as "a" or "an" (e.g., "a" and/or
"an" should be interpreted to mean "at least one" or "one or
more"); the same holds true for the use of definite articles used
to introduce claim recitations. In addition, even if a specific
number of an introduced claim recitation is explicitly recited,
those skilled in the art will recognize that such recitation should
be interpreted to mean at least the recited number (e.g., the bare
recitation of "two recitations," without other modifiers, means at
least two recitations, or two or more recitations). Furthermore, in
those instances where a convention analogous to "at least one of A,
B, and C, etc." is used, in general, such a construction is
intended in the sense one having skill in the art would understand
the convention (e.g., "a system having at least one of A, B, and C"
would include but not be limited to systems that have A alone, B
alone, C alone, A and B together, A and C together, B and C
together, and/or A, B, and C together, etc.). In those instances
where a convention analogous to "at least one of A, B, or C, etc."
is used, in general, such a construction is intended in the sense
one having skill in the art would understand the convention (e.g.,
"a system having at least one of A, B, or C'' would include but not
be limited to systems that have A alone, B alone, C alone, A and B
together, A and C together, B and C together, and/or A, B, and C
together, etc.). It will be further understood by those within the
art that virtually any disjunctive word and/or phrase presenting
two or more alternative terms, whether in the description, claims,
or drawings, should be understood to contemplate the possibilities
of including one of the terms, either of the terms, or both terms.
For example, the phrase "A or B" will be understood to include the
possibilities of "A" or "B" or "A and B."
[0060] As will be understood by one skilled in the art, for any and
all purposes, such as in terms of providing a written description,
all ranges disclosed herein also encompass any and all possible
subranges and combinations of subranges thereof. Any listed range
can be easily recognized as sufficiently describing and enabling
the same range being broken down into at least equal halves,
thirds, quarters, fifths, tenths, etc. As a non-limiting example,
each range discussed herein can be readily broken down into a lower
third, middle third and upper third, etc. As will also be
understood by one skilled in the art all language such as "up to,"
"at least," "greater than," "less than," and the like include the
number recited and refer to ranges which can be subsequently broken
down into subranges as discussed above. Finally, as will be
understood by one skilled in the art, a range includes each
individual member. Thus, for example, a group having 1-3 cells
refers to groups having 1, 2, or 3 cells. Similarly, a group having
1-5 cells refers to groups having 1, 2, 3, 4, or 5 cells, and so
forth.
[0061] While various aspects and embodiments have been disclosed
herein, other aspects and embodiments will be apparent to those
skilled in the art. The various aspects and embodiments disclosed
herein are for purposes of illustration and are not intended to be
limiting, with the true scope and spirit being indicated by the
following claims.
* * * * *