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A concept-based retrieval method for entity-oriented search

机译:面向实体搜索的一种基于概念的检索方法

摘要

Entity-oriented retrieval aims to return a list of relevant entities rather than documents to provide exact answers for user queries. The nature of entity-oriented retrieval requires identifying the semantic intent of user queries, i.e., understanding the semantic role of query terms and determining the semantic categories which indicate the class of target entities. Existing methods are not able to exploit the semantic intent by capturing the semantic relationship between terms in a query and in a document that contains entity related information. To improve the understanding of the semantic intent of user queries, we propose concept-based retrieval method that not only automatically identifies the semantic intent of user queries, i.e., Intent Type and Intent Modifier but introduces concepts represented by Wikipedia articles to user queries. We evaluate our proposed method on entity profile documents annotated by concepts from Wikipedia category and list structure. Empirical analysis reveals that the proposed method outperforms several state-of-the-art approaches.
机译:面向实体的检索旨在返回相关实体的列表,而不是文档,以为用户查询提供准确的答案。面向实体的检索的性质要求识别用户查询的语义意图,即理解查询术语的语义作用并确定指示目标实体类别的语义类别。现有方法无法通过捕获查询和包含实体相关信息的文档中术语之间的语义关系来利用语义意图。为了提高对用户查询语义意图的理解,我们提出了一种基于概念的检索方法,该方法不仅可以自动识别用户查询的语义意图(即意图类型和意图修饰符),而且还可以将Wikipedia文章所代表的概念引入到用户查询中。我们评估了我们建议的方法,该方法针对以Wikipedia类别和列表结构为概念的注释的实体配置文件。实证分析表明,所提出的方法优于几种最先进的方法。

著录项

  • 作者

    Hou Jun; Nayak Richi;

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  • 年度 2013
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