INTERNET SEARCHING USING SEMANTIC DISAMBIGUATION AND EXPANSION

• US 20110202563A1
• Filed: 02/21/2011
• Published: 08/18/2011
• Est. Priority Date: 08/21/2003
• Status: Abandoned Application

• Current Assignee: Idilia, Inc.
• Original Assignee: Idilia, Inc.
• Inventors: COLLEDGE, Matthew, BARNES, Jeremy
• Application Number:
  US13/031,600
• Publication Number:
  US 20110202563A1
• Time in Patent Office: Days
• US Class Current: 707/780
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 40/247 Thesauruses; Synonyms
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99934 Query formulation, input preparation, or translation
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access

Abstract

The invention provides a system and a method of searching for information in a database using a query. In the method, it comprises the steps of: disambiguating the query to identify keyword senses associated with the query; disambiguating information in the database according to the keyword senses; indexing the information in the database according to the keyword senses; expanding the keyword senses to include relevant semantic synonyms for the keyword senses to create a list of expanded keyword senses; searching the database to find relevant information for the query using the expanded keyword senses; and providing search results of the included information containing the keyword senses and other semantically related words senses. The system comprises modules which disambiguate queries and information and indexes the information in a database of word senses.

Claims

1. A method of searching for information in a database using a query, said method comprising the steps of:

a) creating an index containing said information comprising;

disambiguating information in a store of information, said information comprising documents containing text, to identify information keyword meanings, said information keyword meanings comprising meanings of words contained in each respective document and in the context in which said words are used in the respective documents, and indexing said documents in said database according to said information keyword meanings; and

,

b) processing said query comprising;

disambiguating said query to identify query keyword meanings, said query keyword meanings comprising meanings of words contained in said query and in the context in which said words are used in the query;

searching the database to identify matches between the query keyword meanings and the indexed information keyword meanings, identifying documents associated with the matched information keyword meanings, said identified documents comprising information relevant to said query; and

,

providing search results comprising the information relevant to said query.

2. The method of claim 1, wherein steps (a) and (b) are conducted independently of each other.

3. The method of claim 2, wherein step (b) further comprises automatically expanding said query keyword meanings by identifying other word meanings that are semantically related to the query keyword meanings and creating a list of expanded query keyword meanings, wherein said list comprises the query keyword meanings and the identified semantically related word meanings and wherein said list of expanded keyword meanings is used in the step of searching the database.

4. The method of claim 3, wherein said expanding comprises the use of a knowledge base of semantic relationships between word meanings.

5. The method of claim 4, wherein the step of disambiguating the query further comprises assigning probability to said query keyword meanings.

6. A query processing system for providing information relevant to the query comprising:

an input means operable to receive said query;

an output means operable to provide results responsive to said query;

a means for accessing a store of information, said information comprising documents containing text;

a disambiguation module for disambiguating words from an input into an output comprising disambiguated keyword meanings, the disambiguation module being operable on words in the documents and the query whereby words from the documents are disambiguated into information keyword meanings and words from the query are disambiguated into query keyword meanings;

said disambiguation module being operable;

(i) to generate information keyword meanings comprising meanings of words contained in each respective document and in the context in which said words are used in the respective documents and (ii) to generate query keyword meanings comprising meanings of words contained in the query and in the context in which said words are used in the query;

an indexing module for indexing the documents based on the information keyword meanings and for storing said indexed information in a database;

a query processing module for searching the database for matches between the query keyword meanings and the information keyword meanings and for generating query results comprising documents associated with the matched information keyword meanings.

7. The system of claim 6, wherein said query processing module is further operable to automatically expand the query keyword meanings by identifying other word meanings that are semantically related to the query keyword meanings and to create a list of expanded query keyword meanings.

8. The system of claim 7, wherein said query processing module includes a knowledge base of semantic relationships between word meanings and wherein said module uses said knowledge base for expanding the query keyword meanings.

9. The system of claim 6, wherein the store of information comprises the Internet and said documents comprises web pages.

10. A method of searching for information in a database using a query, said method comprising the steps of:

disambiguating information in said database according to keyword senses of words;

indexing said information in said database according to said keyword senses;

disambiguating said query to identify specific keyword senses associated with said query;

expanding said specific keyword senses to include relevant semantic relations for said specific keyword senses to create a list of expanded keyword senses;

searching said database to find relevant information for said query using said expanded keyword senses; and

providing search results of said include information containing the keyword senses and other semantically related words senses.

11. The method of claim 10, wherein disambiguating the query comprises assigning probability to said keyword senses.

12. The method of claim 11, wherein disambiguating said information in said database comprises attaching probabilities to keyword senses.

13. The method claim 12, wherein said disambiguating said query to identify specific keyword senses further comprises utilizing probabilities of each of said specific keyword senses.

14. The method of claim 13, wherein said expanding said specific keyword senses further comprises paraphrasing said query by parsing syntactic structures of said specific keyword sense and identifying additional semantically equivalent queries.

15. The method of claim 14, wherein said keyword senses represent a coarse grouping of fine keyword senses.

16. The method of claim 10, wherein said keyword senses represent a coarse grouping of fine keyword senses.