文章基本信息

标题：Survey of Word Co-occurrence Measures for Collocation Detection
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作者：Olga Kolesnikova
期刊名称：Computación y Sistemas
印刷版ISSN：1405-5546
出版年度：2016
卷号：20
期号：3
页码：327-344
语种：English
出版社：Instituto Politécnico Nacional
其他摘要：This paper presents a detailed survey of word co-occurrence measures used in natural language processing. Word co-occurrence information is vital for accurate computational text treatment, it is important to distinguish words which can combine freely with other words from other words whose preferences to generate phrases are restricted. The latter words together with their typical co-occurring companions are called collocations. To detect collocations, many word cooccurrence measures, also called association measures, are used to determine a high degree of cohesion between words in collocations as opposed to a low degree of cohesion in free word combinations. We describe such association measures grouping them in classes depending on approaches and mathematical models used to formalize word co-occurrence.
其他关键词：Word co-occurrence measure; association measure; collocation; statistical language model; rulebased language model; hybrid approach to model word co-occurrence.