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HyKSS: Hybrid Keyword and Semantic Search

机译:HyKSS:混合关键字和语义搜索

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摘要

Keyword search suffers from a number of issues: ambiguity, synonymy, and an inability to handle semantic constraints. Semantic search helps resolve these issues but is limited by the quality of annotations which are likely to be incomplete or imprecise. Hybrid search, a search technique that combines the merits of both keyword and semantic search, appears to be a promising solution. In this paper we describe and evaluate HyKSS, a hybrid search system driven by extraction ontologies for both annotation creation and query interpretation. For displaying results, HyKSS uses a dynamic ranking algorithm. We show that over data sets of short topical documents, the HyKSS ranking algorithm outperforms both keyword and semantic search in isolation, as well as a number of other non-HyKSS hybrid approaches to ranking.
机译:关键字搜索受许多问题困扰:歧义,同义词和无法处理语义约束。语义搜索有助于解决这些问题,但受到注释质量的限制,注释的质量可能不完整或不精确。混合搜索是一种结合了关键字搜索和语义搜索的优点的搜索技术,似乎是一种很有前途的解决方案。在本文中,我们描述并评估了HyKSS,这是一种由提取本体驱动的混合搜索系统,用于注释创建和查询解释。为了显示结果,HyKSS使用动态排名算法。我们显示,在简短主题文档的数据集上,HyKSS排名算法在孤立性方面优于关键词和语义搜索,以及许多其他非HyKSS混合方法进行排名。

著录项

  • 来源
    《Journal on Data Semantics》 |2015年第4期|213-229|共17页
  • 作者单位

    Department of Computer Science, Brigham Young University, Provo, UT 84602, USA;

    Department of Computer Science, Brigham Young University, Provo, UT 84602, USA;

    Information Systems Department, Brigham Young University, Provo, UT 84602, USA;

    Department of Statistics, Brigham Young University, Provo, UT 84602, USA;

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

  • 入库时间 2022-08-17 23:25:55

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