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Discussions on Subgraph Ranking for Keyworded Search
  • Song, Justin J. ;
  • Kang, Inkyo ;
  • Lee, Wookey ;
  • Kim, Jinho ;
  • Lee, Joo Yeon
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Publication Year
2018-07-01
Journal
Proceedings - IEEE 2018 International Congress on Cybermatics: 2018 IEEE Conferences on Internet of Things, Green Computing and Communications, Cyber, Physical and Social Computing, Smart Data, Blockchain, Computer and Information Technology, iThings/GreenCom/CPSCom/SmartData/Blockchain/CIT 2018
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
Proceedings - IEEE 2018 International Congress on Cybermatics: 2018 IEEE Conferences on Internet of Things, Green Computing and Communications, Cyber, Physical and Social Computing, Smart Data, Blockchain, Computer and Information Technology, iThings/GreenCom/CPSCom/SmartData/Blockchain/CIT 2018, pp.935-936
Mesh Keyword
Data relationshipsGraph informationGraph structuresKeyword searchNon-technical usersPatent informationRelational DatabaseRelevance score
All Science Classification Codes (ASJC)
Business, Management and Accounting (miscellaneous)Artificial IntelligenceComputer Networks and CommunicationsComputer Science ApplicationsHardware and ArchitectureInformation Systems and ManagementHealth InformaticsCommunication
Abstract
Recently many graph information can be available in numerous application domains, including relational database s, Web, Bioinformatics, Chemistry reaction information, Ontol ogy, XML, Social Networks, Patent Information, Paper citatio n, and RDF graphs, etc. Graphs also have structure to be foun d to express complicate data relationships like Web, Database, XML Document and Semantic Web. Traditionally, user had to learn difficult query languages like SQL to do information sear ch over graph structures. There are needs to find out a simple and effective keyword search method for non-Technical users so as to use a keyword search method on the ever-increasing gra ph data. The purpose of this research is to develop a method fo r ranking over the graph structures. We propose the relevance score for each node and link by using each query keyword.
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36272
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85067879585&origin=inward
DOI
https://doi.org/10.1109/cybermatics_2018.2018.00179
Journal URL
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8716290
Type
Conference
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