文章基本信息

标题：A Sketch Algorithm for Estimating Two-Way and Multi-Way Associations
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作者：Ping Li ; Kenneth W. Church
期刊名称：Computational Linguistics
印刷版ISSN：0891-2017
电子版ISSN：1530-9312
出版年度：2007
卷号：33
期号：3
页码：305-354
DOI：10.1162/coli.2007.33.3.305
语种：English
出版社：MIT Press
摘要：We should not have to look at the entire corpus (e.g., the Web) to know if two (or more) words are strongly associated or not. One can often obtain estimates of associations from a small sample. We develop a sketch-based algorithm that constructs a contingency table for a sample. One can estimate the contingency table for the entire population using straightforward scaling. However, one can do better by taking advantage of the margins (also known as document frequencies). The proposed method cuts the errors roughly in half over Broder's sketches.