Words Context Analysis for Improvement of Information Retrieval

被引：0

作者：

Szymanski, Julian ^{[1
]}

机构：

[1] Gdansk Univ Technol, Fac Elect Telecommun & Informat, Dept Comp Syst Architecture, Gdansk, Poland

来源：

COMPUTATIONAL COLLECTIVE INTELLIGENCE - TECHNOLOGIES AND APPLICATIONS, PT I | 2012年 / 7653卷

关键词：

text indexing; information retrieval; semantic indexes;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In the article we present an approach to improvement of retrieval information from large text collections using words context vectors. The vectors have been created analyzing English Wikipedia with Hyperspace Analogue to Language model of words similarity. For test phrases we evaluate retrieval with direct user queries as well as retrieval with context vectors of these queries. The results indicate that the proposed method can not replace retrieval based on direct user queries but it can be used for refining the search results.

引用

页码：318 / 325

页数：8

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