Method for ranking resources using node pool

• US 9,477,766 B2
• Filed: 11/24/2014
• Issued: 10/25/2016
• Est. Priority Date: 06/27/2005
• Status: Active Grant

• Current Assignee: Make Sence Incorporated
• Original Assignee: Make Sence Incorporated
• Inventors: Bobick, Mark, Wimmer, Carl
• Primary Examiner(s): Woo, Isaac M
• Application Number:
  US14/551,938
• Publication Number:
  US 20150302094A1
• Time in Patent Office: 701 Days
• Field of Search: 707600-899
• US Class Current: 1/1
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/3332 Query translation
• CPC Class Codes: G06F 16/334 Query execution G06F16/335 takes precedence
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9538 Presentation of query results
• CPC Class Codes: G06F 16/954 Navigation, e.g. using categorised browsing
• CPC Class Codes: G06F 40/247 Thesauruses; Synonyms
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition

Abstract

An improved search engine creates correlations linking terms from inputs provided by a user to selected target terms. The correlation search process receives pre-processed inputs from a user including a wide variety of input formats including keywords, phrases, sentences, concepts, compound queries, complex queries and orthogonal queries. The pre-processing also includes pre-processing of general digital information objects and static or dynamic generation of questions. After a correlation search of the information presented by the pre-processing, the search results are processed in novel ways to provide an improved relevance ranking of results.

Claims

1. A computer implemented method for generating a ranked plurality of resources based upon at least one input, the method comprising:

decomposing a plurality of resources into a plurality of nodes;

generating an answer space by performing at least one knowledge correlation function on a node pool based upon a plurality of extracted inputs from the at least one input, each node of the node pool comprising a data structure including a subject, an attribute and a bond therebetween, the knowledge correlation function comprising iteratively adding nodes from the node pool onto an end of a chain of nodes by searching the node pool for a match between an attribute of a chained node and a subject of another unchained node in the node pool;

determining a plurality of most significant resources based upon the answer space; and

ranking in significance the plurality of most significant resources to thereby generate the ranked plurality of resources.

2. The method according to claim 1 further comprising performing at least one input evaluation function for generating the plurality of extracted inputs from the at least one input;

and wherein performing the at least one input evaluation function comprises performing a subject evaluation function for extracting subject information from at least one of keywords;

phrases;

sentences;

concepts;

compound, complex and orthogonal inputs; and

a simple web query.

3. The method according to claim 2 wherein performing the subject evaluation function for at least one of keywords and phrases comprises performing a pass through function.

4. The method according to claim 2 wherein performing the subject evaluation function for sentences comprises performing a natural language parser function.

5. The method according to claim 2 wherein performing the subject evaluation function for concepts comprises performing an evaluation for at least one of subject, object and context information.

6. The method according to claim 2 wherein performing the subject evaluation function for at least one of compound, and complex and orthogonal inputs comprises performing a clause recognition function and a natural language parser function.

7. The method according to claim 2 wherein performing the subject evaluation function for a simple web query comprises performing a phrase recognition function.

8. The method according to claim 1 wherein the input comprises a digital information object;

and wherein performing the at least one user input evaluation comprises using a topic detection module adapter and a topic detection module downstream therefrom.

9. The method according to claim 8 wherein performing the at least one user input evaluation further comprises using a natural language parser downstream from the topic detection module.

10. The method according to claim 1 further comprising performing a question generating function to obtain the at least one input for defining a query.

11. The method according to claim 1 wherein the most significant resources are transitively associated with the at least one input through resources used to create the answer space.

12. The method according to claim 1 wherein determining the plurality of most significant resources does not use a similarity measure.

13. A physical non-transitory computer-readable medium having instructions stored thereon which, when executed by a computer, cause the computer to perform a method for generating a ranked plurality of resources based upon at least one input, the method comprising:

decomposing a plurality of resources into a plurality of nodes;

generating an answer space by performing at least one knowledge correlation function on a node pool based upon a plurality of extracted inputs from the at least one input, each node of the node pool comprising a data structure including a subject, an attribute and a bond therebetween, the knowledge correlation function comprising iteratively adding nodes from the node pool onto an end of a chain of nodes by searching the node pool for a match between an attribute of a chained node and a subject of another unchained node in the node pool;

determining a plurality of most significant resources based upon the answer space; and

ranking in significance the plurality of most significant resources to thereby generate the ranked plurality of resources.

14. The physical non-transitory computer-readable medium according to claim 13 wherein the method further comprises performing at least one input evaluation function for generating the plurality of extracted inputs from the at least one input;

and wherein performing the at least one input evaluation function comprises performing a subject evaluation function for extracting subject information from at least one of keywords;

phrases;

sentences;

concepts;

compound, complex or orthogonal inputs; and

a simple web query.

15. The physical non-transitory computer-readable medium according to claim 14 wherein performing the subject evaluation function for at least one of keywords and phrases comprises performing a pass through function.

16. The physical non-transitory computer-readable medium according to claim 14 wherein performing the subject evaluation function for sentences comprises performing a natural language parser function.

17. The physical non-transitory computer-readable medium according to claim 14 wherein performing the subject evaluation function for concepts comprises performing an evaluation for at least one of subject, object and context information.

18. The physical non-transitory computer-readable medium according to claim 14 wherein performing the subject evaluation function for at least one of compound, complex and orthogonal inputs comprises performing a clause recognition function and a natural language parser function.

19. The physical non-transitory computer-readable medium according to claim 14 wherein performing the subject evaluation function for a simple web query comprises performing a phrase recognition function.

20. The physical non-transitory computer-readable medium according to claim 13 further comprising performing a question generating function to obtain the at least one input for defining a query.