Extreme value theory applied to document retrieval from large collections

被引：0

作者：

David Madigan

Yehuda Vardi

Ishay Weissman

机构：

[1] Avaya Labs,

[2] Rutgers University,undefined

[3] Technion,undefined

来源：

Information Retrieval | 2006年 / 9卷

关键词：

very large corpus IR; extreme value theory; precision at K;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

We consider text retrieval applications that assign query-specific relevance scores to documents drawn from particular collections. Such applications represent a primary focus of the annual Text Retrieval Conference (TREC), where the participants compare the empirical performance of different approaches. P(K), the proportion of the top K documents that are relevant, is a popular measure of retrieval effectiveness.

引用

页码：273 / 294

页数：21

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