METHOD AND DEVICE FOR PROVIDING SEARCH ENGINE LABEL

• US 20150331953A1
• Filed: 07/24/2015
• Published: 11/19/2015
• Est. Priority Date: 01/24/2013
• Status: Abandoned Application

• Current Assignee: Beijing Jingdong Century Trading Co., Ltd.
• Original Assignee: Beijing Jingdong Century Trading Co., Ltd.
• Inventors: SHEN, Wei, LIU, Shangkun
• Application Number:
  US14/808,215
• Publication Number:
  US 20150331953A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/245 Query processing
• CPC Class Codes: G06F 16/24564 Applying rules; Deductive queries
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9532 Query formulation
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

A method and device for providing a search engine label are disclosed. In one aspect, the method includes extracting one or more attribute words from a sentence and performing a dependence relationship analysis on the sentence to obtain, for each attribute word, a dependence relationship path from the attribute word to a viewpoint word. The method further includes extracting the viewpoint words corresponding respectively to each of the attribute words in the sentence based on the dependence relationship path and using the attribute words and the viewpoint words to compose the search engine label.

Claims

1. A method for providing a search engine label, comprising:

extracting one or more attribute words from a sentence;

performing a dependence relationship analysis on the sentence to obtain a dependence relationship path, with respect to each of the attribute words, from each of the attribute words to a corresponding viewpoint word;

extracting the viewpoint words respectively corresponding to each of the attribute words in the sentence based on the dependence relationship path; and

using the attribute words and the viewpoint words to compose the search engine label.

2. The method according to claim 1, wherein prior to the extracting the one or more attribute words from the sentence, the method further comprises:

filtering text data based on a preset rule; and

acquiring a sentence from the text data.

3. The method according to claim 2, wherein the acquiring the sentence from the text data comprises:

performing a clause division on the text data based on punctuation included in the text data to obtain short clauses; and

acquiring the short clauses to serve as the sentence.

4. The method according to claim 1, wherein the performing the dependence relationship analysis on the sentence to obtain the dependence relationship path, with respect to each of the attribute words, from each of the attribute words to a corresponding viewpoint word comprises:

performing the dependence relationship analysis on the sentence to obtain a series of dependence relationships of the sentence;

obtaining, for each of the attribute words, the dependence relationship from the attribute word to the corresponding viewpoint word via the series of dependence relationships, based on the attribute words and the series of dependence relationships; and

traversing the dependence relationships containing the viewpoint words to thereby obtain the dependence relationship path.

5. The method according to claim 1, wherein the extracting the viewpoint words respectively corresponding to each of the attribute words in the sentence based on the dependence relationship path comprises:

selecting a dependence relationship path having a comparatively high occurrence frequency from the dependence relationship paths;

obtaining a dependence relationship rule based on the selected dependence relationship path; and

extracting the viewpoint words corresponding to the respective attribute words in the sentence based on the dependence relationship rule.

6. The method according to claim 1, wherein after the using the attribute words and the viewpoint words to compose the search engine label, the method further comprises combining a plurality of labels containing synonymous viewpoint words into one label based on a synonymy of the viewpoint words.

7. A device for providing a search engine label, comprising:

an attribute word extraction module for extracting one or more attribute words from a sentence;

a dependence relationship analysis module for performing a dependence relationship analysis on the sentence to obtain, for each of the attribute words, a dependence relationship path from the attribute word to a corresponding viewpoint word;

a viewpoint word extraction module for extracting the viewpoint words respectively corresponding to each of the attribute words in the sentence based on the dependence relationship path; and

a search engine label module for using the attribute words and the viewpoint words to compose the search engine label.

8. The device according to claim 7, further comprising a preprocessing module for filtering text data based on a preset rule, and then acquiring a sentence from the text data.

9. The device according to claim 8, wherein the preprocessing module is further for performing a clause division on the text data based on punctuation included in the text data to obtain short clauses, and then acquiring the short clauses to serve as the sentence.

10. The device according to claim 7, wherein the dependence relationship analysis module is further for:

performing the dependence relationship analysis on the sentence to obtain a series of dependence relationships of the sentence;

obtaining, for each of the attribute words, the dependence relationship from the attribute word to the corresponding viewpoint word via the series of dependence relationships, based on the attribute words and the series of dependence relationships; and

traversing the dependence relationships containing the viewpoint words to thereby obtain the dependence relationship path.

11. The device according to claim 7, wherein the viewpoint word extraction module is further for:

selecting a dependence relationship path having a comparatively high occurrence frequency from the dependence relationship paths;

obtaining a dependence relationship rule based on the selected dependence relationship path; and

extracting the viewpoint words corresponding to the respective attribute words in the sentence based on the dependence relationship rule.

12. The device according to claim 7, further comprising a normalization module for combining a plurality of labels containing synonymous viewpoint words into one label based on a synonymy of the viewpoint words.