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A linguistically driven framework for query expansion via grammatical constituent highlighting and role-based concept weighting

机译：语言驱动的语法扩展突出显示和基于角色的概念加权的查询扩展框架

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摘要

In this paper, we propose a linguistically-motivated query expansion framework that recognizes and encodes significant query constituents characterizing query intent in order to improve retrieval performance. Concepts-of-Interest are recognized as the core concepts that represent the gist of the search goal whilst the remaining query constituents which serve to specify the search goal and complete the query structure are classified as descriptive, relational or structural. Acknowledging the need to form semantically-associated base pairs for the purpose of extracting related potential expansion concepts, an algorithm which capitalizes on syntactical dependencies to capture relationships between adjacent and non-adjacent query concepts is proposed. Lastly, a robust weighting scheme that duly emphasizes the importance of query constituents based on their linguistic role within the expanded query is presented. We demonstrate improvements in retrieval effectiveness in terms of increased mean average precision garnered by the proposed linguistic-based query expansion framework through experimentation on the TREC ad hoc test collections.
机译：在本文中，我们提出了一种基于语言的查询扩展框架，该框架可识别和编码表征查询意图的重要查询成分，以提高检索性能。兴趣概念被认为是代表搜索目标要旨的核心概念，而用于指定搜索目标并完成查询结构的其余查询组成部分则分为描述性，关系性或结构性。认识到需要形成语义相关的碱基对，以提取相关的潜在扩展概念，提出了一种利用句法依赖性来捕获相邻查询概念与非相邻查询概念之间关系的算法。最后，提出了一种健壮的加权方案，该方案根据其在扩展查询中的语言作用适当强调了查询成分的重要性。我们通过对TREC临时测试集合进行实验，证明了所提出的基于语言的查询扩展框架所提高的平均平均精度，从而提高了检索效率。

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