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Answering who/when, what, how, why through constructing data graph, information graph, knowledge graph and wisdom graph

  • Lixu Shao
  • , Yucong Duan
  • , Xiaobing Sun
  • , Honghao Gao
  • , Donghai Zhu
  • , Weikai Miao
  • Hainan University
  • Yangzhou University
  • Shanghai University
  • East China Normal University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Knowledge graphs have been widely adopted, in large part owing to their schema-less nature. It enables knowledge graphs to grow seamlessly and allows for new relationships and entities as needed. Natural language questions are the most intuitive way of formulating an information need. People can formulate questions to express their information needs. Natural language questions as a query language present an ideal compromise between keyword and structured querying. Questions can be used to express complex information needs that cannot be expressed as keywords without a significant loss in structure and semantics. Knowledge graph has abundant natural semantics and can contain various and more complete information. Its expression mechanism is closer to natural language. We propose to clarify the expression of knowledge graph as a whole.We use knowledge graph to solve the Five Ws problems respectively which are guided by interrogative words such as who/when, what, how and why. We also propose to specify knowledge graph in a progressive manner as four basic forms including data graph, information graph, knowledge graph and wisdom graph.

源语言英语
主期刊名Proceedings - SEKE 2017
主期刊副标题29th International Conference on Software Engineering and Knowledge Engineering
出版商Knowledge Systems Institute Graduate School
1-6
页数6
ISBN(电子版)1891706411
DOI
出版状态已出版 - 2017
活动29th International Conference on Software Engineering and Knowledge Engineering, SEKE 2017 - Pittsburgh, 美国
期限: 5 7月 20177 7月 2017

出版系列

姓名Proceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE
ISSN(印刷版)2325-9000
ISSN(电子版)2325-9086

会议

会议29th International Conference on Software Engineering and Knowledge Engineering, SEKE 2017
国家/地区美国
Pittsburgh
时期5/07/177/07/17

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