Classification of news by topic using location data

Zolzaya Dashdorj, Muhammad Tahir Khan, Loris Bozzato, Sang-Geun Lee

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

3 Citations (Scopus)

Abstract

In this work, we will consider news articles to determine geolocalization of their information and classify their topics on the basis of an available open data source: OpenStreetMap (OSM). We propose a knowledge-based conceptual and computational approach that disambiguates place names (i.e., geo-objects and regions) mentioned in news articles in terms of geographic coordinates. The geo-located news articles are analyzed to identify local topics: we found that the mentioned geo-objects are a good proxy to classify news topics.

Original languageEnglish
Title of host publicationSemantic Technology - 6th Joint International Conference, JIST 2016, Revised Selected Papers
PublisherSpringer Verlag
Pages305-314
Number of pages10
Volume10055 LNCS
ISBN (Print)9783319501116
DOIs
Publication statusPublished - 2016
Event6th Joint International Conference on Semantic Technology, JIST 2016 - Singapore, Singapore
Duration: 2016 Nov 22016 Nov 4

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10055 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other6th Joint International Conference on Semantic Technology, JIST 2016
CountrySingapore
CitySingapore
Period16/11/216/11/4

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Dashdorj, Z., Khan, M. T., Bozzato, L., & Lee, S-G. (2016). Classification of news by topic using location data. In Semantic Technology - 6th Joint International Conference, JIST 2016, Revised Selected Papers (Vol. 10055 LNCS, pp. 305-314). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10055 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-50112-3_23