Semantic text search

• US 10,324,967 B2
• Filed: 11/16/2017
• Issued: 06/18/2019
• Est. Priority Date: 09/22/2014
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: Zelevinsky, Vladimir, Dashevsky, Yevgeniy, Ye, Diana
• Primary Examiner(s): Abebe, Daniel
• Application Number:
  US15/814,976
• Publication Number:
  US 20180075132A1
• Time in Patent Office: 579 Days
• Field of Search: 704 9
• CPC Class Codes: G06F 16/3329 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 16/3338 Query expansion
• CPC Class Codes: G06F 16/3344 using natural language analysis
• CPC Class Codes: G06F 16/338 Presentation of query results
• CPC Class Codes: G06F 40/211 Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars
• CPC Class Codes: G06F 40/30 Semantic analysis

Abstract

A system for performing semantic search receives an electronic text corpus and separates the text corpus into a plurality of sentences. The system parses and converts each sentence into a sentence tree. The system receives a search query and matches the search query with one or more of the sentence trees.

Claims

1. A non-transitory computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to perform a semantic search, the semantic search comprising:

receiving an electronic text corpus;

separating the text corpus into a plurality of sentences;

parsing and converting each sentence into a sentence tree;

receiving a search query via a user interface;

matching the search query with one or more of the sentence trees; and

in response to the matching, extracting sentiments for the search query that correspond to the matched sentence trees.

2. The computer-readable medium of claim 1, the semantic search further comprising:

converting the search query into a query tree, wherein the matching comprises matching the query tree with one or more of the sentence trees.

3. The computer-readable medium of claim 1, further comprising:

in response to the matching, providing documents from the text corpus that correspond to the matched sentence trees.

4. The computer-readable medium of claim 1, further comprising:

in response to the matching, providing refinements to the search query that correspond to the matched sentence trees.

5. The computer-readable medium of claim 1, wherein the search query comprises a search term and the extracting sentiments for the search query comprises retrieving modifiers from the matched sentence trees that are linked to the search term.

6. The computer-readable medium of claim 5, wherein modifiers that are linked to the search term are identified by identifying edges from a node that corresponds to the search term on the matched sentence trees.

7. The computer-readable medium of claim 2, wherein the user interface displays hypernym matching for the query tree.

8. The computer-readable medium of claim 1, further comprising modifying one or more of the sentence trees, wherein each sentence tree comprises nodes and at least one edge, and the modifying comprises at least one of:

expanding a node, collapsing a node, expanding an edge, or collapsing an edge.

9. A method of performing a semantic search, the method comprising:

receiving an electronic text corpus;

separating the text corpus into a plurality of sentences;

parsing and converting each sentence into a sentence tree;

receiving a search query via a user interface;

matching the search query with one or more of the sentence trees; and

in response to the matching, extracting sentiments for the search query that correspond to the matched sentence trees.

10. The method of claim 9, further comprising:

converting the search query into a query tree, wherein the matching comprises matching the query tree with one or more of the sentence trees.

11. The method of claim 9, further comprising:

in response to the matching, providing documents from the text corpus that correspond to the matched sentence trees.

12. The method of claim 9, further comprising:

in response to the matching, providing refinements to the search query that correspond to the matched sentence trees.

13. The method of claim 9, wherein the search query comprises a search term and the extracting sentiments for the search query comprises retrieving modifiers from the matched sentence trees that are linked to the search term.

14. The method of claim 13, wherein modifiers that are linked to the search term are identified by identifying edges from a node that corresponds to the search term on the matched sentence trees.

15. The method of claim 10, wherein the user interface displays hypernym matching for the query tree.

16. The method of claim 9, further comprising modifying one or more of the sentence trees, wherein each sentence tree comprises nodes and at least one edge, and the modifying comprises at least one of:

expanding a node, collapsing a node, expanding an edge, or collapsing an edge.

17. A semantic text search query system comprising:

a processor;

a storage device coupled to the processor, wherein the storage device stores a plurality of sentence trees that are formed by separating a text corpus into a plurality of sentences and parsing and converting each sentence into one of the sentence trees;

wherein the processor is adapted to generate a user interface that receives a search query; and

the processor is adapted to match the search query with one or more of the sentence trees and, in response to the matching, extracting sentiments for the search query that correspond to the matched sentence trees.

18. The semantic text search query system of claim 17, the processor further adapted to convert the search query into a query tree, wherein the matching comprises matching the query tree with one or more of the sentence trees.

19. The semantic text search query system of claim 17, the processor further adapted to, in response to the matching, providing documents from the text corpus that correspond to the matched sentence trees.

20. The semantic text search query system of claim 17 wherein the search query comprises a search term and the extracting sentiments for the search query comprises retrieving modifiers from the matched sentence trees that are linked to the search term.