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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - SEKE 2017
Subtitle of host publication29th International Conference on Software Engineering and Knowledge Engineering
PublisherKnowledge Systems Institute Graduate School
Pages1-6
Number of pages6
ISBN (Electronic)1891706411
DOIs
StatePublished - 2017
Event29th International Conference on Software Engineering and Knowledge Engineering, SEKE 2017 - Pittsburgh, United States
Duration: 5 Jul 20177 Jul 2017

Publication series

NameProceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE
ISSN (Print)2325-9000
ISSN (Electronic)2325-9086

Conference

Conference29th International Conference on Software Engineering and Knowledge Engineering, SEKE 2017
Country/TerritoryUnited States
CityPittsburgh
Period5/07/177/07/17

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