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.
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收藏
页码：273 / 294
页数：21
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