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Is the unigram relevance model term independent? Classifying term dependencies in query expansion

机译:会标相关性模型术语是否独立?在查询扩展中对术语依赖性进行分类

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摘要

This paper develops a framework for classifying term dependencies in query expansion with respect to the role terms play in structural linguistic associations. The framework is used to classify and compare the query expansion terms produced by the unigram and positional relevance models. As the unigram relevance model does not explicitly model term dependencies in its estimation process it is often thought to ignore dependencies that exist between words in natural language. ududThe framework presented in this paper is underpinned by two types of linguistic association, namely syntagmatic and paradigmatic associations. It was found that syntagmatic associations were a more prevalent form of linguistic association used in query expansion. Paradoxically, it was the unigram model that exhibited this association more than the positional relevance model. This surprising finding has two potential implications for information retrievaludmodels: udud(1) if linguistic associations underpin query expansion, then a probabilistic term dependence assumption based on position is inadequate for capturing them; udud(2) the unigram relevance model captures more term dependency information than its underlying theoretical model suggests, so its normative position as a baseline that ignores term dependencies should perhaps be reviewed.
机译:本文针对术语在结构语言关联中的作用,开发了一个框架,用于对查询扩展中的术语依赖性进行分类。该框架用于分类和比较由unigram和位置相关性模型产生的查询扩展项。由于单字组相关性模型没有在其估计过程中显式建模术语依赖项,因此通常认为它会忽略自然语言中单词之间存在的依赖项。 ud ud本文介绍的框架以两种类型的语言关联为基础,即标记性关联和范式关联。已经发现,语法关联是查询扩展中使用的语言关联的更普遍形式。矛盾的是,与位置相关性模型相比,单字组模型更能显示这种关联。这个令人惊讶的发现对信息检索有两个潜在的影响 udmodel: ud ud(1)如果语言关联支撑查询扩展,则基于位置的概率术语依赖假设不足以捕获它们; ud ud(2)会标相关性模型比其基础理论模型所建议的捕获了更多的术语相关性信息,因此也许应审查其作为忽略术语相关性的基线的规范位置。

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