Automatic Generation of Event Ontology from Social Network and Mobile Positioning Data

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

2 Citations (Scopus)

Abstract

The study of mobile positioning data makes it possible to detect whether an event has happened at a particular place during a given period. However, determining the nature and details of the event is a challenge, especially if the event is not widely known, as is the case for local events. We propose an approach to determining the nature of local events by generating an ontology in a completely automatic way from social network data and data on people's movements and by querying this generated ontology. This approach uses entity discovery techniques, filtering systems and information enrichment via Open Data, as well as a system for matching discovered entities and ontology elements. Evaluation via a survey allowed us to validate approximately that the information presented in the ontology is reliable, makes sense and answers our questions.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2021
PublisherAssociation for Computing Machinery
Pages87-94
Number of pages8
ISBN (Electronic)9781450391153
DOIs
Publication statusPublished - Dec 14 2021
Event2021 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2021 - Virtual, Online, Australia
Duration: Dec 14 2021Dec 17 2021

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2021 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2021
Country/TerritoryAustralia
CityVirtual, Online
Period12/14/2112/17/21

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

Fingerprint

Dive into the research topics of 'Automatic Generation of Event Ontology from Social Network and Mobile Positioning Data'. Together they form a unique fingerprint.

Cite this