Information retrieval on Turkish texts

被引：58

作者：

Can, Fazli ^{[1
]}

Kocberber, Seyit ^{[1
]}

Balcik, Erman ^{[1
]}

Kaynak, Cihan ^{[1
]}

Ocalan, H. Cagdas ^{[1
]}

Vursavas, Onur M. ^{[1
]}

机构：

[1] Bilkent Univ, Dept Comp Engn, Bilkent Informat Retrieval Grp, TR-06800 Ankara, Turkey

来源：

JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY | 2008年 / 59卷 / 03期

关键词：

D O I：

10.1002/asi.20750

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this study, we investigate information retrieval (IR) on Turkish texts using a large-scale test collection that contains 408,305 documents and 72 ad hoc queries. We examine the effects of several stemming options and query-document matching functions on retrieval performance. We show that a simple word truncation approach, a word truncation approach that uses language-dependent corpus statistics, and an elaborate lemmatizer-based stemmer provide similar retrieval effectiveness in Turkish IR. We investigate the effects of a range of search conditions on the retrieval performance; these include scalability issues, query and document length effects, and the use of stopword list in indexing.

引用

页码：407 / 421

页数：15

共 62 条

[1] Indexing strategies for Swedish full text retrieval under different user scenarios [J].