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
EditorsJun Sun, Yang Liu, Jin Song Dong, Grigoris Antoniou, Zhe Wang, Wei Hu, Yuan-Fang Li
PublisherSpringer Verlag
Pages305-314
Number of pages10
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)0302-9743
ISSN (Electronic)1611-3349

Other

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

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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