Enhancing topic tracking with temporal information

Baoli Li, Wenjie Li, Qin Lu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

6 Citations (Scopus)

Abstract

In this paper, we propose a new strategy with time granularity reasoning for utilizing temporal information in topic tracking. Compared with previous ones, our work has four distinguished characteristics. Firstly, we try to determine a set of topic times for a target topic from the given on-topic stories. It helps to avoid the negative influence from other irrelevant times. Secondly, we take into account time granularity variance when deciding whether a coreference relationship exists between two times. Thirdly, both publication time and times presented in texts are considered. Finally, as time is only one attribute of a topic, we increase the similarity between a story and a target topic only when they are related not only temporally but also semantically. Experiments on two TDT corpora show that our method makes good use of temporal information in news stories.
Original languageEnglish
Title of host publicationProceedings of the Twenty-Ninth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Pages667-668
Number of pages2
Volume2006
Publication statusPublished - 31 Oct 2006
Event29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval - Seatttle, WA, United States
Duration: 6 Aug 200611 Aug 2006

Conference

Conference29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
CountryUnited States
CitySeatttle, WA
Period6/08/0611/08/06

Keywords

  • Temporal information processing
  • Topic tracking

ASJC Scopus subject areas

  • Engineering(all)
  • Information Systems
  • Software
  • Applied Mathematics

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