Clustering and mapping related news about violence events on their time-lines

Syed Toufeeq Ahmed, Sukru Tikves, Hasan Davulcu

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

Abstract

Keeping track of news stories and events as they progress can be a tedious job, but as every day routine most of the web users read and follow many stories and events in news. If an analyst in her area has to follow and map all these according to the time-line they happen, the task quickly becomes overwhelming. We present an online tool which attempts to ease the analyst's task of finding all news articles about an event, and sorting and mapping them on a time-line. We implemented an incremental clustering algorithm working on real-time incoming news, experimenting with different feature sets, including named entities and sentence overlap methods. We evaluated these approaches using Document Understand Conference (DUC) datasets.

Original languageEnglish (US)
Title of host publicationISI 2010 - 2010 IEEE International Conference on Intelligence and Security Informatics: Public Safety and Security
Pages175
Number of pages1
DOIs
StatePublished - 2010
Event2010 IEEE International Conference on Intelligence and Security Informatics: Public Safety and Security, ISI 2010 - Vancouver, BC, Canada
Duration: May 23 2010May 26 2010

Other

Other2010 IEEE International Conference on Intelligence and Security Informatics: Public Safety and Security, ISI 2010
CountryCanada
CityVancouver, BC
Period5/23/105/26/10

Fingerprint

Sorting
Clustering algorithms
Violence

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Safety, Risk, Reliability and Quality

Cite this

Ahmed, S. T., Tikves, S., & Davulcu, H. (2010). Clustering and mapping related news about violence events on their time-lines. In ISI 2010 - 2010 IEEE International Conference on Intelligence and Security Informatics: Public Safety and Security (pp. 175). [5484742] https://doi.org/10.1109/ISI.2010.5484742

Clustering and mapping related news about violence events on their time-lines. / Ahmed, Syed Toufeeq; Tikves, Sukru; Davulcu, Hasan.

ISI 2010 - 2010 IEEE International Conference on Intelligence and Security Informatics: Public Safety and Security. 2010. p. 175 5484742.

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

Ahmed, ST, Tikves, S & Davulcu, H 2010, Clustering and mapping related news about violence events on their time-lines. in ISI 2010 - 2010 IEEE International Conference on Intelligence and Security Informatics: Public Safety and Security., 5484742, pp. 175, 2010 IEEE International Conference on Intelligence and Security Informatics: Public Safety and Security, ISI 2010, Vancouver, BC, Canada, 5/23/10. https://doi.org/10.1109/ISI.2010.5484742
Ahmed ST, Tikves S, Davulcu H. Clustering and mapping related news about violence events on their time-lines. In ISI 2010 - 2010 IEEE International Conference on Intelligence and Security Informatics: Public Safety and Security. 2010. p. 175. 5484742 https://doi.org/10.1109/ISI.2010.5484742
Ahmed, Syed Toufeeq ; Tikves, Sukru ; Davulcu, Hasan. / Clustering and mapping related news about violence events on their time-lines. ISI 2010 - 2010 IEEE International Conference on Intelligence and Security Informatics: Public Safety and Security. 2010. pp. 175
@inproceedings{de31ee27c7f848239d6592a2140a2a1d,
title = "Clustering and mapping related news about violence events on their time-lines",
abstract = "Keeping track of news stories and events as they progress can be a tedious job, but as every day routine most of the web users read and follow many stories and events in news. If an analyst in her area has to follow and map all these according to the time-line they happen, the task quickly becomes overwhelming. We present an online tool which attempts to ease the analyst's task of finding all news articles about an event, and sorting and mapping them on a time-line. We implemented an incremental clustering algorithm working on real-time incoming news, experimenting with different feature sets, including named entities and sentence overlap methods. We evaluated these approaches using Document Understand Conference (DUC) datasets.",
author = "Ahmed, {Syed Toufeeq} and Sukru Tikves and Hasan Davulcu",
year = "2010",
doi = "10.1109/ISI.2010.5484742",
language = "English (US)",
isbn = "9781424464609",
pages = "175",
booktitle = "ISI 2010 - 2010 IEEE International Conference on Intelligence and Security Informatics: Public Safety and Security",

}

TY - GEN

T1 - Clustering and mapping related news about violence events on their time-lines

AU - Ahmed, Syed Toufeeq

AU - Tikves, Sukru

AU - Davulcu, Hasan

PY - 2010

Y1 - 2010

N2 - Keeping track of news stories and events as they progress can be a tedious job, but as every day routine most of the web users read and follow many stories and events in news. If an analyst in her area has to follow and map all these according to the time-line they happen, the task quickly becomes overwhelming. We present an online tool which attempts to ease the analyst's task of finding all news articles about an event, and sorting and mapping them on a time-line. We implemented an incremental clustering algorithm working on real-time incoming news, experimenting with different feature sets, including named entities and sentence overlap methods. We evaluated these approaches using Document Understand Conference (DUC) datasets.

AB - Keeping track of news stories and events as they progress can be a tedious job, but as every day routine most of the web users read and follow many stories and events in news. If an analyst in her area has to follow and map all these according to the time-line they happen, the task quickly becomes overwhelming. We present an online tool which attempts to ease the analyst's task of finding all news articles about an event, and sorting and mapping them on a time-line. We implemented an incremental clustering algorithm working on real-time incoming news, experimenting with different feature sets, including named entities and sentence overlap methods. We evaluated these approaches using Document Understand Conference (DUC) datasets.

UR - http://www.scopus.com/inward/record.url?scp=77954781097&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77954781097&partnerID=8YFLogxK

U2 - 10.1109/ISI.2010.5484742

DO - 10.1109/ISI.2010.5484742

M3 - Conference contribution

AN - SCOPUS:77954781097

SN - 9781424464609

SP - 175

BT - ISI 2010 - 2010 IEEE International Conference on Intelligence and Security Informatics: Public Safety and Security

ER -