INCREMENTAL REASONING BASED ON SCALABLE AND DYNAMICAL SEMANTIC DATA

• US 20150199607A1
• Filed: 05/31/2013
• Published: 07/16/2015
• Est. Priority Date: 05/31/2013
• Status: Abandoned Application

• Current Assignee: Streamline Licensing LLC (IP Edge LLC)
• Original Assignee: Empire Technology Development LLC (Allied Inventors Management, LLC)
• Inventors: Fang, Jun
• Application Number:
  US14/410,056
• Publication Number:
  US 20150199607A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06N 5/04 Inference or reasoning models

Abstract

Technologies are generally described for performing a reasoning task based on a set of semantic data. In some examples, a method and a system for process a scalable and dynamical set of semantic data are described. The method may include extracting, by an incremental reasoning system, a first set of relevant data from the set of semantic data based on the reasoning task. The method may include generating, by the incremental reasoning system, a first set of reasoning results by performing the reasoning task based on the first set of relevant data. The method may further include maintaining, by the incremental reasoning system, a relevance tree based on the first set of relevant data, wherein the incremental reasoning system is configured to extract a second set of relevant data from the set of semantic data based on the relevance tree and generate a second set of reasoning results based on the second set of relevant data.

Claims

1. A method for performing a reasoning task based on a set of semantic data, the method comprising:

extracting, by an incremental reasoning system, a first set of relevant data from the set of semantic data based on the reasoning task;

generating, by the incremental reasoning system, a first set of reasoning results by performing the reasoning task based on the first set of relevant data; and

maintaining, by the incremental reasoning system, a relevance tree based on the first set of relevant data, wherein the incremental reasoning system is configured to extract a second set of relevant data from the set of semantic data based on the relevance tree and generate a second set of reasoning results based on the second set of relevant data.

2. The method of claim 1, further comprising:

extracting, by the incremental reasoning system, the second set of relevant data from the set of semantic data based on the relevance tree;

generating, by the incremental reasoning system, a second set of reasoning results by performing the reasoning task based on the second set of relevant data; and

updating, by the incremental reasoning system, the relevance tree based on the second set of relevant data, wherein the incremental reasoning system is configured to extract a third set of relevant data from the set of semantic data based on the updated relevance tree and generate a third set of reasoning results based on the third set of relevant data.

3. The method of claim 1, wherein extracting the first set of relevant data comprises:

utilizing a resolvable relevance function to extract the first set of relevant data from the set of semantic data for being relevant to the reasoning task.

4. The method of claim 2, wherein extracting the second set of relevant data comprises:

utilizing a resolvable relevance function to extract the second set of relevant data from the set of semantic data for being relevant to a leaf node of the relevance tree.

5. The method of claim 1, wherein generating the first set of results comprises:

for each node in the relevance tree,

performing the reasoning task to obtain a subset of reasoning results based on a corresponding set of relevant data that is associated with the node, and

including the subset of reasoning results in the first set of reasoning results.

6. The method of claim 1, wherein maintaining the relevance tree comprises:

associating a root node of the relevance tree with the reasoning task;

constructing a first node as a child node of the root node; and

associating the first node with the first set of relevant data.

7. The method of claim 6, wherein updating the relevance tree comprises

constructing a second node as a child node of the first node;

and

associating the second node with the second set of relevant data.

8. The method of claim 1, wherein maintaining the relevance tree comprises:

storing a set of source relationships between the first set of relevant data and the set of semantic data in the relevance tree; and

storing a set of result relationships between the first set of relevant data and the first set of reasoning results in the relevance tree.

9. The method of claim 8, further comprising:

detecting, by the incremental reasoning system, a change made to a piece of data in the set of semantic data, wherein the piece of data is identified from the set of semantic data for affecting the relevance tree and the first set of reasoning results; and

updating, by the incremental reasoning system, the relevance tree and the first set of reasoning results that are affected by the change, wherein the incremental reasoning system is configured to generate a third set of reasoning results based on the updated relevant tree.

10. The method of claim 9, wherein updating the resolvable relevance tree and the first set of reasoning results comprises

identifying a first node in the relevance tree for having the source relationship with the piece of data;

upon a determination that the change is a modification or a deletion, removing the first node and its child nodes from the relevance tree; and

removing a subset of reasoning results from the first set of reasoning results, wherein the subset of reasoning results are identified for having result relationships with the first node and its child nodes.

11. The method of claim 10, wherein updating the resolvable relevance tree and the first set of reasoning results further comprises:

upon a determination that the change is a modification, adding a second node in replacement of the first node in the relevance tree, wherein the incremental reasoning system is configured to utilize the second node when generating the third set of reasoning results based on the updated relevant tree.

12. A method for performing a reasoning task based on a set of semantic data, the method comprising:

performing, by an incremental reasoning system, the reasoning task by incrementally

extracting a corresponding set of relevant data from the set of semantic data,

generating a corresponding set of reasoning results based on the corresponding set of relevant data, and

maintaining a relevance tree based on the corresponding set of relevant data, and

concurrent to the performing of the reasoning task, monitoring, by the incremental reasoning system, the set of semantic data for changes that may affect the corresponding set of reasoning results.

13. The method of claim 12, wherein extracting the corresponding set of relevant data comprises:

in a first iteration, extracting the corresponding set of relevant data from the set of semantic data for being relevant to the reasoning task; and

in a second iteration subsequent to the first iteration,

extracting the corresponding set of relevant data for the set of semantic data for being relevant to a leaf node of the relevance tree, and

updating the relevance tree based on the corresponding set of relevant data.

14. The method of claim 12, wherein maintaining the relevance tree comprises:

storing a set of source relationships between the corresponding set of relevant data and the set of semantic data in the relevance tree; and

storing a set of result relationships between the corresponding set of relevant data and the corresponding set of reasoning results in the relevance tree.

15. The method of claim 14, further comprising:

detecting a change made to a piece of data in the set of semantic data, wherein the piece of data is identified from the set of semantic data based on the set of source relationships; and

updating the relevance tree and the corresponding set of reasoning results that are affected by the change based on the set of result relationships.

16. A system for performing a reasoning task based on a set of semantic data, the system comprising:

a scalable data processing module configured to extract a first set of relevant data from the set of semantic data based on the reasoning task, and construct a relevance tree based on the first set of relevant data;

a reasoning module coupled with the scalable data processing module, wherein the reasoning module is configured to generate a first set of reasoning results by performing the reasoning task based on the first set of relevant data; and

a dynamical data processing module configured to operate concurrently along with the scalable data processing module to monitor the set of semantic data for changes that may affect the first set of reasoning results.

17. The system as recited in claim 16, wherein scalable data processing module is further configured to

extract the first set of relevant data based on the reasoning task in a first iteration, and

extract a second set of relevant data from the set of semantic data based on the relevance tree in a second iteration subsequent to the first iteration.

18. The system as recited in claim 17, wherein

the scalable data processing module is further configured to update the relevance tree based on the second set of relevant data, and

the reasoning module is further configured to generate a second set of reasoning results by performing the reasoning task based on the second set of relevant data.

19. The system as recited in claim 16, wherein the dynamical data processing module is further configured to

update the relevance tree and the first set of reasoning results upon a detection of a change in the set of semantic data that affects the first set of reasoning results.

20. A non-transitory machine-readable medium having a set of instructions which, when executed by a processor, cause the processor to perform a method for performing a reasoning task based on a set of semantic data, the method comprising:

extracting, by an incremental reasoning system, a first set of relevant data from the set of semantic data based on the reasoning task;

generating, by the incremental reasoning system, a first set of reasoning results by performing the reasoning task based on the first set of relevant data; and

maintaining, by the incremental reasoning system, a relevance tree based on the first set of relevant data, wherein the incremental reasoning system is configured to extract a second set of relevant data from the set of semantic data based on the relevance tree and generate a second set of reasoning results based on the second set of relevant data.