Inverted table for storing and querying conceptual indices

• US 9,703,858 B2
• Filed: 07/14/2014
• Issued: 07/11/2017
• Est. Priority Date: 07/14/2014
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Franceschini, Michele M., Soares, Livio B., Wegman, Mark N., Lastras-Montano, Luis A.
• Primary Examiner(s): Le, Uyen
• Application Number:
  US14/330,438
• Publication Number:
  US 20160012092A1
• Time in Patent Office: 1,093 Days
• Field of Search: None
• CPC Class Codes: G06F 16/325 Hash tables
• CPC Class Codes: G06F 16/3346 using probabilistic model
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques

Abstract

According to an aspect, storing and querying conceptual indices (CIs) includes creating a conceptual inverted index (CII) from the CIs. The CII includes CII entries, each of which corresponds to a concept in a concept graph. Creating the CII includes populating each entry with pointers to documents selected from the CIs having likelihoods of being related to the concept that are greater than a threshold value, and the corresponding likelihoods. An aspect also includes receiving a query that includes a concept in the concept graph, and generating query results from a search that include at least a subset of the pointers to documents. Each of the CIs is associated with a corresponding document and includes a CI entry for each concept in the concept graph, and each of the CI entries specifies a value indicating a likelihood that the document is related to the concept in the concept graph.

Claims

1. A computer program product comprising:

a tangible storage medium readable by a processing circuit and storing instructions for execution by the processing circuit to perform a method comprising;

creating a conceptual inverted index (CII) based on conceptual indices (CIs), the CII including CII entries, each of which corresponds to a separate concept in a concept graph, the creating including for each CII entry;

with respect to the concept corresponding to the CII entry, populating the CII entry with;

pointers to documents selected from the CIs having likelihoods of being related to the concept that are greater than a threshold value; and

the corresponding likelihoods of the documents;

receiving a query that includes one of the concepts in the concept graph as a search term;

searching the CII for the search term;

generating query results from the searching, the query results including at least a subset of the pointers to documents;

creating an explanations index that indicates for each of the documents pointed to by the pointers included in the query results, a likelihood that each of one or more concepts extracted from the document is related to the search term; and

generating an explanation of the query results based on the explanations index, the explanation including a summary of a relevance of the query results to the query,

wherein each of the CIs is associated with a corresponding one of the documents and includes a CI entry for each concept in the concept graph, and each of the CI entries specifies a value indicating a likelihood that the one of the documents is related to the concept in the concept graph.

2. The computer program product of claim 1, wherein the query results include a pointer to a document that does not explicitly mention the search term.

3. The computer program product of claim 1, wherein the at least one CI entry indicates a document having a likelihood of being related to a concept in the concept graph that is not mentioned in the document.

4. The computer program product of claim 1, wherein the query results only include pointers to documents having likelihoods greater than a second threshold of being related to the concept included in the search term.

5. The computer program product of claim 1, wherein each document is associated with a valid version number and the generating query results includes verifying that any pointers to documents correspond to documents that match the associated valid version numbers.

6. The computer program product of claim 1, wherein a document is related to a concept in the concept graph if a concept extracted from the document is connected to the concept in the concept graph via a path in the concept graph.

7. The computer program product of claim 1, wherein the summary includes an excerpt of text.

8. The computer program product of claim 1, wherein the summary includes contents of the explanations index.

9. A system comprising:

a memory having computer readable computer instructions; and

a processor for executing the computer readable instructions, the computer readable instructions including;

creating a conceptual inverted index (CII) based on conceptual indices (CIs), the CII including CII entries, each of which corresponds to a separate concept in a concept graph, the creating including for each CII entry;

with respect to the concept corresponding to the CII entry, populating the CII entry with;

pointers to documents selected from the CIs having likelihoods of being related to the concept that are greater than a threshold value; and

the corresponding likelihoods of the documents;

receiving a query that includes one of the concepts in the concept graph as a search term;

searching the CII for the search term;

generating query results from the searching, the query results including at least a subset of the pointers to documents;

creating an explanations index that indicates for each of the documents pointed to by the pointers included in the query results, a likelihood that each of one or more concepts extracted from the document is related to the search term; and

generating an explanation of the query results based on the explanations index, the explanation including a summary of a relevance of the query results to the query,

wherein each of the CIs is associated with a corresponding one of the documents and includes a CI entry for each concept in the concept graph, and each of the CI entries specifies a value indicating a likelihood that the one of the documents is related to the concept in the concept graph.

10. The system of claim 9, wherein the query results include a pointer to a document that does not explicitly mention the search term.

11. The system of claim 9, wherein the at least one CI entry indicates a document having a likelihood of being related to a concept in the concept graph that is not mentioned in the document.

12. The system of claim 9, wherein the query results only include pointers to documents having likelihoods greater than a second threshold of being related to the concept included in the search term.

13. The system of claim 9, wherein each document is associated with a valid version number and the generating query results includes verifying that any pointers to documents correspond to documents that match the associated valid version numbers.

14. The system of claim 9, wherein the summary includes an excerpt of text.

15. The system of claim 9, wherein the summary includes contents of the explanations index.