面向ScholarSpace知识库的关键词查询方法

李和瀚; 孟小峰; 邹磊

doi:10.11959/j.issn.1000-436x.2015312

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面向ScholarSpace知识库的关键词查询方法

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- 面向ScholarSpace知识库的关键词查询方法
- Keyword search approach for knowledge base in ScholarSpace
- 通信学报 2015年36卷第12期页码：28-36
- 作者机构：
  
  1. 中国人民大学信息学院，北京 100872
  2. 北京大学计算机科学技术研究所，北京 100871
- 作者简介：
  
  [ "李和瀚（1990-），男，四川成都人，中国人民大学硕士生，主要研究方向为知识图谱上的自然语言查询、本体构建。" ]
  [ "孟小峰（1964-），男，河北邯郸人，中国人民大学教授、博士生导师，主要研究方向为Web数据管理、移动数据管理、大数据。" ]
  [ "邹磊（1980-），男，安徽安庆人，北京大学副教授，主要研究方向为图数据管理、基于RDF的知识库管理。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61379050);国家自然科学基金资助项目(91224008);中国人民大学科学研究基金资助项目(11XNL010)
- DOI：10.11959/j.issn.1000-436x.2015312
  中图分类号： TP311.1
- 网络出版日期：2015-12，
  
  纸质出版日期：2015-12-25
- 稿件说明：
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李和瀚, 孟小峰, 邹磊. 面向ScholarSpace知识库的关键词查询方法[J]. 通信学报, 2015,36(12):28-36.

He-han LI, Xiao-feng MENG, Lei ZOU. Keyword search approach for knowledge base in ScholarSpace[J]. Journal on communications, 2015, 36(12): 28-36.
李和瀚, 孟小峰, 邹磊. 面向ScholarSpace知识库的关键词查询方法[J]. 通信学报, 2015,36(12):28-36. DOI： 10.11959/j.issn.1000-436x.2015312.

He-han LI, Xiao-feng MENG, Lei ZOU. Keyword search approach for knowledge base in ScholarSpace[J]. Journal on communications, 2015, 36(12): 28-36. DOI： 10.11959/j.issn.1000-436x.2015312.

摘要

知识库中存储着大量关于真实世界中的实体信息及实体之间的关系，随着规模的不断增长，其应用也愈发广泛。另一方面，由于大量互联网用户通过关键词描述问题和查询意图，因此如何让知识库具备更好的关键词查询应答能力，成为了研究的热点。从中文知识库的构建入手，提出了一套完整的面向中文限定领域知识库的关键词检索框架，实现并改进了基于模板的关键词查询转换方法，提出了基于语义的知识库释义和实体索引方法，提高了关键词映射能力。同时在SPARQL转换过程中采用了缺失关系索引，提高了转换成功率，提升了能够处理的查询数量。同时在学术空间ScholarSpace上对该框架进行了系统实现，取得了良好的应用效果。

Abstract

Knowledge bases (KB) store large amount of structured information about the entities and their relationships.As the scale of KBs increased

their application also varied.On the other side

large amount of users describe their question or query intention by submitting keyword queries.Thus enabling KB to answer these keyword queries becomes of crucial importance.A framework from building a Chinese KB to answering keyword search over it was established.A novel approach based on query template to translate the keyword queries into structured queries was proposed.A semantic based paraphrase and index approach to improve the result of query term mapping and an absent predicate index to deal with the predicate absence during the query translation step was proposed.Significant improvement of the ability of translating keyword query to structured query was achieved.Finally the framework and approach was implemented in the ScholarSpace system and get a good performance.

关键词

Keywords

references

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