Automatic query recommendation using click-through data

被引：0

作者：

Dupret, Georges ^{[1
]}

Mendoza, Marcelo ^{[2
]}

机构：

[1] Yahoo Res Latin Amer, Blanco Encalada 2120, Santiago, Chile

[2] Univ Valparaiso, Dept Comp Sci, Valparaiso, Chile

来源：

PROFESSIONAL PRACTICE IN ARTIFICIAL INTELLIGENCE | 2006年 / 218卷

关键词：

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：

We present a method to help a user redefine a query suggesting a list of similar queries. The method proposed is based on click-through data were sets of similar queries could be identified. Scientific literature shows that similar queries are useful for the identification of. different information needs behind a query. Unlike most previous work, in this paper we are focused on the discovery of better queries rather than related queries. We will show with experiments over real data that the identification of better queries is useful for query disambiguation and query specialization.

引用

页码：303 / +

页数：2

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