A Query Expansion Technique Using the EWC Semantic Relatedness Measure

被引：0

作者：

Klyuev, Vitaly ^{[1
]}

Haralambous, Yannis ^{[2
]}

机构：

[1] Univ Aizu, Aizu Wakamatsu, Fukushima 9658580, Japan

[2] Inst Telecom Telecom Bretagne, Dept Informat, Lab STICC Technopole Brest Iroise, UMR CNRS 3192, F-29238 Brest 3, France

来源：

INFORMATICA-JOURNAL OF COMPUTING AND INFORMATICS | 2011年 / 35卷 / 04期

关键词：

relatedness measure; Wikipedia; WordNet; search engine; query expansion;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

This paper analyses the efficiency of the EWC semantic relatedness measure in an ad-hoc retrieval task. This measure combines the Wikipedia-based Explicit Semantic Analysis (ESA) measure, the WordNet path measure and the mixed collocation index. EWC considers encyclopaedic, ontological, and collocational knowledge about terms. This advantage of EWC is a key factor to find precise terms for automatic query expansion. In the experiments, the open source search engine Terrier is utilised as a tool to index and retrieve data. The proposed technique is tested on the NTCIR data collection. The experiments demonstrated superiority of EWC over ESA.

引用

页码：401 / 406

页数：6

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