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Enquiry statement analytical method and system for information retrieval

A query statement and analysis method technology, applied in the field of information retrieval, can solve problems such as insufficiently clear user query needs

Inactive Publication Date: 2009-08-19
PEKING UNIV
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AI Technical Summary

Problems solved by technology

However, these systems only analyze the word meaning at the vocabulary level, which is not enough to clarify the user's query needs, and should further analyze the syntax and semantics at the sentence level

Method used

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  • Enquiry statement analytical method and system for information retrieval
  • Enquiry statement analytical method and system for information retrieval

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Embodiment Construction

[0033] Next, through a specific example, that is, the user enters the query sentence "does the latest Apple computer support the function of handwriting input", to describe the specific implementation of the system and the working process of each module in detail.

[0034] 1. Lexical analysis

[0035] Automatic word segmentation and named entity recognition

[0036] Word segmentation is the basis for further analysis of query statements by other modules. The present invention adopts the conditional random field model to jointly mark the two tasks of word segmentation and named entity recognition, that is, to mark the position and entity category of each word in the sentence, and then convert the result of word segmentation and identify the named entity . The conditional random field model can flexibly integrate various features reflecting context information and word formation features, and is suitable for sequence labeling tasks such as word segmentation. This joint strateg...

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Abstract

The invention discloses a query sentence analyzing method based on understanding of natural languages and a system thereof, and belongs to the technical field of information retrieval. The query sentence analyzing method comprises the following steps: (1) automatic segmenting, named entity identification and part-of-speech tagging of an input Chinese query sentence are implemented; (2) syntax structure of the segmented sentence is analyzed so as to obtain a syntax structural tree, and meaning of each word is determined according to the sentence after the part-of-speech tagging; (3) according to the syntax structure and the meaning of each word, semantic roles of predicates in the sentence are tagged; and (4) according to the analyzed result of the sentence from the levels of syntactics, syntax and semantics, keywords are expanded and the keywords that can reflect user information retrieval requirements are extracted. The query sentence analyzing system of the invention comprises a syntactic analyzing module, a syntax analyzing module, a semantic analyzing module and a keyword extracting module. The query sentence analyzing method and system can greatly improve the accuracy of query results and provide desired query results for users.

Description

technical field [0001] The invention relates to the technical field of information retrieval, in particular to a query statement analysis method and system based on natural language understanding. Background technique [0002] With the rapid development and maturity of the Internet on a global scale, the information resources on the network are constantly enriched, and the amount of information data is also expanding rapidly. In today's society, searching for information on the Internet through search engines has become the main way for modern people to obtain information. Therefore, providing users with more convenient and effective query services has become the current and future development direction of search engine technology. [0003] At present, the query method accepted by most search engines is still keyword query. This query method requires users to summarize their personal query intentions into several most effective words, which not only increases the burden on...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06F17/20G06F40/00
Inventor 吴玺宏迟惠生罗定生林小俊张猛
Owner PEKING UNIV
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