论文标题
通过语法组成的突出显示和基于角色的概念加权的语言驱动的框架，用于查询扩展
A Linguistically Driven Framework for Query Expansion via Grammatical Constituent Highlighting and Role-Based Concept Weighting
论文作者
论文摘要
在本文中，我们提出了一个语言动机的查询扩展框架，该框架识别并编码了重要的查询成分，这些查询成分表征了查询意图，以提高检索性能。利益概念被认为是代表搜索目标要旨的核心概念，而其余的查询成分来指定搜索目标并完成查询结构被归类为描述性，关系或结构。为了提取相关的潜在扩展概念而形成语义相关的基础对，提出了一种算法，该算法利用了句法依赖性，以捕获相邻和非贴发查询概念之间的关系。最后，提出了一个强大的加权方案，它根据其在扩展的查询中的语言作用而适当强调查询成分的重要性。我们证明了通过提出的基于语言的查询扩展框架获得的平均平均精度（MAP）的提高，从而提高了检索有效性，这是通过对TREC Ad Hoc测试集合进行的。
In this paper, we propose a linguistically-motivated query expansion framework that recognizes and en-codes significant query constituents that characterize 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 (MAP) garnered by the proposed linguistic-based query expansion framework through experimentation on the TREC ad hoc test collections.
