SEARCH TECHNOLOGY USING SYNONIMS AND PARAPHRASING

• US 20160004766A1
• Filed: 09/17/2015
• Published: 01/07/2016
• Est. Priority Date: 10/10/2006
• Status: Abandoned Application

• Current Assignee: ABBYY Production LLC (ABBYY Software)
• Original Assignee: ABBYY InfoPoisk LLC
• Inventors: Danielyan, Tatiana, Indenbom, Evgeny
• Application Number:
  US14/857,649
• Publication Number:
  US 20160004766A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/3344 using natural language analysis
• CPC Class Codes: G06F 40/237 Lexical tools
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06F 40/58 Use of machine translation, e.g. for multi-lingual retrieval, for server-side translation for client devices or for real-time translation

Abstract

The present invention is a method and a system of organizing information searches in electronic text corpora and displaying the search results in the user interface. The system and the method enable searches not just for words or word combinations, but also for specific lexical meanings of words, where a lexical meaning is a realization of a word'"'"'s semantic meaning in a particular language. The completeness of search results is bases on incorporation synonyms and paraphrases in the search. The method also includes searching for fragments matching the query in electronic text corpora, estimating the results and the displaying the results ranked to the user.

Claims

1. A method of organizing a search in electronic text corpora for computer system, with the following actions carried out at least once:

performing a semantic-syntactic analysis of a search query, comprising building a ranked list of possible lexical meanings for at least one word of the search query;

compiling a list of synonyms for at least one lexical meaning from the ranked list of possible lexical meanings of the at least one word of the search query;

ranking synonyms from the list of synonyms for the at least one lexical meaning;

generating query versions based on the ranked synonyms;

calculating a rating of correspondence of the query versions to the search query;

searching for text fragments in the electronic text corpora satisfying the query based on at least one of the query versions;

ranking the found text fragments based on the ratings of correspondence of the query versions to the search query.

2. The method of claim 1, further comprising

preliminary generating at least one index of words from the text corpora;

and

saving the index of words in a memory.

3. The method of claim 1, further comprising:

conducting preliminary semantic and syntactic analysis of the text corpora comprising determining lexical meanings of words in sentences from the text corpora;

constructing a semantic structures of the sentences from the textcorpora;

storing in memory results of the semantic and syntactic analysis; and

indexing the text corpora based on the semantic structures and storing the indexes.

4. The method of claim 2, further comprising

performing a semantic-syntactic analysis of the text fragments to determine most probable lexical meanings of the words in the sentences;

and

assessment of correspondence of lexical meanings of words in found fragments to lexical meanings of words in the variation of source query.

5. The method of claim 3, further comprising:

computing aggregated assessment of correspondence of the found fragment to the query version; and

ranking the fragments in accordance with the rating of their corresponding query version of the search query and the value of aggregated assessment of correspondence of the found fragment to the query version.

6. The method of claim 4, further comprising:

computing aggregated assessment of correspondence of the found fragment to the query version; and

ranking the fragments in accordance with the rating of their corresponding query version of the search query and the value of aggregated assessment of correspondence of the found fragment to the query version.

7. The method of claim 1, wherein the semantic and syntactic analysis of the search query comprises building a semantic structure of the search query.

8. The method of claim 7, further comprising building search query versions based on paraphrases of at least a part of the search query.

9. The method of claim 8, wherein the paraphrases of at least the part of the search query are obtained as a synthesis of at least one fragment in natural language based on at least one fragment of the semantic structure obtained based on the semantic-syntactic analysis of the search query.

10. The method of claim 9, wherein the obtained paraphrases are ranked based on degree of semantic proximity to the search query.

11. A system for organizing a search in electronic text corpora of natural language texts, the system comprising:

one or more data processors; and

one or more storage devices storing instructions that, when executed by the one or more data processors, cause the one or more data processors to perform operations comprising;

performing a semantic-syntactic analysis of a search query, comprising building a ranked list of possible lexical meanings for at least one word of the search query;

compiling a list of synonyms for at least one lexical meaning from the ranked list of possible lexical meanings of the at least one word of the search query;

ranking synonyms from the list of synonyms for the at least one lexical meaning;

generating query versions based on the ranked synonyms;

calculating a rating of correspondence of the query versions to the search query;

searching for text fragments in the electronic text corpora satisfying the query based on at least one of the query versions;

ranking the found text fragments based on the ratings of correspondence of the query versions to the search query.

12. The system of claim 11, further comprising preliminary generating at least one index of words from the text corpora;

and saving the index of words in a memory.

13. The system of claim 11, further comprising:

conducting preliminary semantic and syntactic analysis of the text corpora comprising determining lexical meanings of words in sentences from the text corpora;

constructing a semantic structures of the sentences from the text corpora;

storing in memory results of the semantic and syntactic analysis; and

indexing the text corpora based on the semantic structures and storing the indexes.

14. The system of claim 12, further comprising:

performing a semantic-syntactic analysis of the text fragments to determine most probable lexical meanings of the words in the sentences; and

assessment of correspondence of lexical meanings of words in found fragments to lexical meanings of words in the variation of source query.

15. The system of claim 13, further comprising:

computing aggregated assessment of correspondence of the found fragment to the query version; and

ranking the fragments in accordance with the rating of their corresponding query version of the search query and the value of aggregated assessment of correspondence of the found fragment to the query version.

16. The system of claim 14, further comprising:

computing aggregated assessment of correspondence of the found fragment to the query version; and

ranking the fragments in accordance with the rating of their corresponding query version of the search query and the value of aggregated assessment of correspondence of the found fragment to the query version.

17. The system of claim 11, wherein the semantic and syntactic analysis of the search query comprises building a semantic structure of the search query.

18. The system of claim 17, further comprising building search query versions based on paraphrases of at least a part of the search query.

19. The system of claim 18, wherein the paraphrases of at least the part of the search query are obtained as a synthesis of at least one fragment in natural language based on at least one fragment of the semantic structure obtained based on the semantic-syntactic analysis of the search query.

20. The system of claim 19, wherein the obtained paraphrases are ranked based on degree of semantic proximity to the search query.