Coupling of semantic and syntactic graphs generated via tweets to detect local events

Landy Rajaonarivo, Tsunenori Mine, Yutaka Arakawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Local events are important for the local people, tourists and local authorities. However, information about them is limited, or even absent on official websites. We propose an approach to automatically generate a data graph on local events via social network and mobile positioning data. This graph is constructed by the research results of syntactic and semantic data collection and will be used for an intelligent local event recommendation application. The coupling of these two research results makes it possible to discover little-known events or places that are not in the Linked Open Data and at the same time to connect them to it. An online experiment was set up to evaluate the performance of the techniques used in the study on semantic data which concerns the automatic ontology generation. The results allow us to conclude that the performance of the Named Entity Recognition and the choice of threshold score in automatic ontology generation depend on the categories of detected words types.

Original languageEnglish
Title of host publicationProceedings - 2022 12th International Congress on Advanced Applied Informatics, IIAI-AAI 2022
EditorsTokuro Matsuo, Kunihiko Takamatsu, Yuichi Ono
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages128-133
Number of pages6
ISBN (Electronic)9781665497558
DOIs
Publication statusPublished - 2022
Event12th International Congress on Advanced Applied Informatics, IIAI-AAI 2022 - Kanazawa, Japan
Duration: Jul 2 2022Jul 7 2022

Publication series

NameProceedings - 2022 12th International Congress on Advanced Applied Informatics, IIAI-AAI 2022

Conference

Conference12th International Congress on Advanced Applied Informatics, IIAI-AAI 2022
Country/TerritoryJapan
CityKanazawa
Period7/2/227/7/22

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Decision Sciences (miscellaneous)

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