Knowledge correlation search engine

• US 8,140,559 B2
• Filed: 06/27/2006
• Issued: 03/20/2012
• 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): Mofiz, Apu
• Assistant Examiner(s): Rahman, Mohammad
• Application Number:
  US11/426,932
• Publication Number:
  US 20070005566A1
• Time in Patent Office: 2,093 Days
• Field of Search: 707/708, 707/769, 707/761
• US Class Current: 707/761
• 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 16/9538 Presentation of query results
• 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 displaying a ranked plurality of resources based upon at least one user supplied input, the method comprising:

performing at least one input evaluation function for generating a plurality of extracted inputs from the at least one user supplied input;

decomposing a plurality of resources into a plurality of nodes using natural language parsing to perform word classification based upon parts of speech;

generating an answer space by performing at least one knowledge correlation function on a node pool based upon the plurality of extracted inputs, each node of the node pool comprising a data structure sufficient to independently convey meaning and 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;

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

displaying the ranked plurality of resources.

2. The method according to claim 1 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.

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, 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 user supplied 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 user supplied input for defining a query.

11. The method according to claim 10 wherein performing the question generating function comprises generating a static menu of questions.

12. The method according to claim 10 wherein performing the question generating function comprises generating a dynamic menu of questions.

13. The method according to claim 10 wherein the query is in a canonical form.

14. The method according to claim 1 wherein the most significant resources are strongly associated with resources identified from the answer space.

15. The method according to claim 1 wherein the most significant resources are strongly associated with resources used to create the answer space.

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

17. The method according to claim 1 wherein relevancy of the ranked plurality of resources is guaranteed by the existence of an answer space.

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

19. A physical computer-readable medium having instructions stored thereon which, when executed by a computer, cause the computer to perform an information retrieval method comprising:

performing at least one input evaluation function for generating a plurality of extracted inputs from at least one user supplied input;

decomposing a plurality of resources into a plurality of nodes using natural language parsing to perform word classification based upon parts of speech;

generating an answer space by performing at least one knowledge correlation function on a node pool based upon the plurality of extracted inputs, each node of the node pool comprising a data structure sufficient to independently convey meaning and 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;

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

displaying the ranked plurality of resources.

20. The physical computer-readable medium according to claim 19 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.

21. The physical computer-readable medium according to claim 20 wherein performing the subject evaluation function for at least one of keywords and phrases comprises performing a pass through function.

22. The physical computer-readable medium according to claim 20 wherein performing the subject evaluation function for sentences comprises performing a natural language parser function.

23. The physical computer-readable medium according to claim 20 wherein performing the subject evaluation function for concepts comprises performing an evaluation for at least one of subject, object and context information.

24. The physical computer-readable medium according to claim 20 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.

25. The physical computer-readable medium according to claim 20 wherein performing the subject evaluation function for a simple web query comprises performing a phrase recognition function.

26. The physical computer-readable medium according to claim 19 further comprising performing a question generating function to obtain the at least one user supplied input for defining a query.

27. The physical computer-readable medium according to claim 19 wherein the most significant resources are strongly associated with resources identified from the answer space.

28. The physical computer-readable medium according to claim 19 wherein the most significant resources are strongly associated with resources used to create the answer space.

29. The physical computer-readable medium according to claim 19 wherein the most significant resources are transitively associated with the at least one user supplied input through resources used to create the answer space.

30. The physical computer-readable medium according to claim 19 wherein determining the plurality of most significant resources does not use a similarity measure.

31. A computer implemented method for displaying a ranked plurality of resources based upon at least one user supplied input, the method comprising:

performing at least one input evaluation function for generating a plurality of extracted inputs from the at least one user supplied input;

decomposing a plurality of resources into a plurality of nodes using an intermediate format wherein a first term is paired with a second term based upon a relation defined by a context comprising at least one of a schema, a tree graph, and a directed graph;

generating an answer space by performing at least one knowledge correlation function on a node pool based upon the plurality of extracted inputs, each node of the node pool comprising a data structure sufficient to independently convey meaning and 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;

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

displaying the ranked plurality of resources.

32. The method according to claim 31 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.

33. The method according to claim 32 wherein performing the subject evaluation function for at least one of keywords and phrases comprises performing a pass through function.

34. A physical computer-readable medium having instructions stored thereon which, when executed by a computer, cause the computer to perform an information retrieval method comprising:

performing at least one input evaluation function for generating a plurality of extracted inputs from at least one user supplied input;

decomposing a plurality of resources into a plurality of nodes using an intermediate format wherein a first term is paired with a second term based upon a relation defined by a context comprising at least one of a schema, a tree graph, and a directed graph;

generating an answer space by performing at least one knowledge correlation function on a node pool based upon the plurality of extracted inputs, each node of the node pool comprising a data structure sufficient to independently convey meaning and 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;

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

displaying the ranked plurality of resources.

35. The physical computer-readable medium according to claim 34 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.

36. The physical computer-readable medium according to claim 35 wherein performing the subject evaluation function for at least one of keywords and phrases comprises performing a pass through function.