Classification of news by topic using location data

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

doi:10.1007/978-3-319-50112-3_23

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 proceeding › Conference 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 language	English
Title of host publication	Semantic Technology - 6th Joint International Conference, JIST 2016, Revised Selected Papers
Publisher	Springer Verlag
Pages	305-314
Number of pages	10
Volume	10055 LNCS
ISBN (Print)	9783319501116
DOIs	https://doi.org/10.1007/978-3-319-50112-3_23
Publication status	Published - 2016
Event	6th Joint International Conference on Semantic Technology, JIST 2016 - Singapore, Singapore Duration: 2016 Nov 2 → 2016 Nov 4

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10055 LNCS
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Other

Other	6th Joint International Conference on Semantic Technology, JIST 2016
Country	Singapore
City	Singapore
Period	16/11/2 → 16/11/4

Fingerprint

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

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

Classification of news by topic using location data. / Dashdorj, Zolzaya; Khan, Muhammad Tahir; Bozzato, Loris; Lee, Sang-Geun.

Semantic Technology - 6th Joint International Conference, JIST 2016, Revised Selected Papers. Vol. 10055 LNCS Springer Verlag, 2016. p. 305-314 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10055 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Dashdorj, Z, Khan, MT, 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, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10055 LNCS, Springer Verlag, pp. 305-314, 6th Joint International Conference on Semantic Technology, JIST 2016, Singapore, Singapore, 16/11/2. https://doi.org/10.1007/978-3-319-50112-3_23

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

Dashdorj, Zolzaya ; Khan, Muhammad Tahir ; Bozzato, Loris ; Lee, Sang-Geun. / Classification of news by topic using location data. Semantic Technology - 6th Joint International Conference, JIST 2016, Revised Selected Papers. Vol. 10055 LNCS Springer Verlag, 2016. pp. 305-314 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{ffc4dfe7d4d64fdabb2c279e2cb0ebbf,

title = "Classification of news by topic using location data",

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.",

author = "Zolzaya Dashdorj and Khan, {Muhammad Tahir} and Loris Bozzato and Sang-Geun Lee",

year = "2016",

doi = "10.1007/978-3-319-50112-3_23",

language = "English",

isbn = "9783319501116",

volume = "10055 LNCS",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "305--314",

booktitle = "Semantic Technology - 6th Joint International Conference, JIST 2016, Revised Selected Papers",

note = "6th Joint International Conference on Semantic Technology, JIST 2016 ; Conference date: 02-11-2016 Through 04-11-2016",

}

TY - GEN

T1 - Classification of news by topic using location data

AU - Dashdorj, Zolzaya

AU - Khan, Muhammad Tahir

AU - Bozzato, Loris

AU - Lee, Sang-Geun

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85006858112&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85006858112&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-50112-3_23

DO - 10.1007/978-3-319-50112-3_23

M3 - Conference contribution

AN - SCOPUS:85006858112

SN - 9783319501116

VL - 10055 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 305

EP - 314

BT - Semantic Technology - 6th Joint International Conference, JIST 2016, Revised Selected Papers

PB - Springer Verlag

T2 - 6th Joint International Conference on Semantic Technology, JIST 2016

Y2 - 2 November 2016 through 4 November 2016

ER -

Access to Document

10.1007/978-3-319-50112-3_23