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Automatic suggestion of phrasal-concept queries for literature search

机译:短语概念查询的自动建议,用于文献检索

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摘要

Both general and domain-specific search engines have adopted query suggestion techniques to help users formulate effective queries. In the specific domain of literature search (e.g., finding academic papers), the initial queries are usually based on a draft paper or abstract, rather than short lists of keywords. In this paper, we investigate phrasal-concept query suggestions for literature search. These suggestions explicitly specify important phrasal concepts related to an initial detailed query. The merits of phrasal-concept query suggestions for this domain are their readability and retrieval effectiveness: (1) phrasal concepts are natural for academic authors because of their frequent use of terminology and subject-specific phrases and (2) academic papers describe their key ideas via these subject-specific phrases, and thus phrasal concepts can be used effectively to find those papers. We propose a novel phrasal-concept query suggestion technique that generates queries by identifying key phrasal-concepts from pseudo-labeled documents and combines them with related phrases. Our proposed technique is evaluated in terms of both user preference and retrieval effectiveness. We conduct user experiments to verify a preference for our approach, in comparison to baseline query suggestion methods, and demonstrate the effectiveness of the technique with retrieval experiments.
机译:通用搜索引擎和特定于域的搜索引擎都采用了查询建议技术来帮助用户制定有效的查询。在文献搜索的特定领域(例如,查找学术论文),最初的查询通常基于草稿或摘要,而不是关键字的简短列表。在本文中,我们调查了用于文学搜索的短语概念查询建议。这些建议明确指定了与初始详细查询有关的重要短语概念。短语概念查询建议在该领域的优点在于其可读性和检索效率:(1)短语概念由于经常使用术语和特定于主题的短语而对于学术作者而言是很自然的;(2)学术论文描述了其关键思想通过这些特定于主题的短语,因此短语概念可以有效地用于查找那些论文。我们提出了一种新颖的短语概念查询建议技术,该技术可通过识别伪标签文档中的关键短语概念并将其与相关短语组合来生成查询。我们提出的技术是根据用户偏好和检索效率进行评估的。与基准查询建议方法相比,我们进行了用户实验,以验证对我们方法的偏爱,并通过检索实验证明该技术的有效性。

著录项

  • 来源
    《Information Processing & Management》 |2014年第4期|568-583|共16页
  • 作者单位

    Center for Intelligent Information Retrieval, School of Computer Science, University of Massachusetts Amherst, 140 Governors Drive, Amherst, MA 01003, USA;

    Center for Intelligent Information Retrieval, School of Computer Science, University of Massachusetts Amherst, 140 Governors Drive, Amherst, MA 01003, USA;

    Center for Intelligent Information Retrieval, School of Computer Science, University of Massachusetts Amherst, 140 Governors Drive, Amherst, MA 01003, USA;

    Center for Intelligent Information Retrieval, School of Computer Science, University of Massachusetts Amherst, 140 Governors Drive, Amherst, MA 01003, USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Query suggestion; Phrasal-concept query; Literature search;

    机译:查询建议;短语概念查询;文献检索;

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