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A relevance-based topic model for news event tracking

Published: 19 July 2009 Publication History

Abstract

Event tracking is the task of discovering temporal patterns of popular events from text streams. Existing approaches for event tracking have two limitations: scalability and inability to rule out non-relevant portions in text streams. In this study, we propose a novel approach to tackle these limitations. To demonstrate the approach, we track news events across a collection of weblogs spanning a two-month time period.

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Blei, M., Ng, A., Jordan, M., Latent Dirichlet Allocation, Journal of Machine Learning Research, 3, 2003.
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Mei, Q., Zhai, C., Discovering Evolutionary Theme Patterns from Text -- An Exploration of Temporal Text Mining, The 11th ACM SIGKDD, 2005.
[3]
Ha-Thuc, V., Srinivasan, P. Topic Models and a Revisit of Text-Related Applications, The 2nd ACM PIKM, 2008.
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Apache Lucene. http://lucene.apache.org/
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Spinn3r. http://spinn3r.com/
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Wikipedia. http://www.wikipedia.org/

Cited By

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  • (2018)Lifecycle-Based Event Detection from MicroblogsCompanion Proceedings of the The Web Conference 201810.1145/3184558.3186338(283-290)Online publication date: 23-Apr-2018
  • (2017)News event evolution model based on the reading willingness and modified TF-IDF formulaJournal of High Speed Networks10.3233/JHS-17055523:1(33-47)Online publication date: 1-Jan-2017
  • (2016)Measuring the Semantic Uncertainty of News Events for Evolution Potential EstimationACM Transactions on Information Systems10.1145/290371934:4(1-25)Online publication date: 9-Jun-2016
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Published In

cover image ACM Conferences
SIGIR '09: Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
July 2009
896 pages
ISBN:9781605584836
DOI:10.1145/1571941

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 July 2009

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Author Tags

  1. LDA
  2. event tracking
  3. relevance models
  4. topic models

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

View all
  • (2018)Lifecycle-Based Event Detection from MicroblogsCompanion Proceedings of the The Web Conference 201810.1145/3184558.3186338(283-290)Online publication date: 23-Apr-2018
  • (2017)News event evolution model based on the reading willingness and modified TF-IDF formulaJournal of High Speed Networks10.3233/JHS-17055523:1(33-47)Online publication date: 1-Jan-2017
  • (2016)Measuring the Semantic Uncertainty of News Events for Evolution Potential EstimationACM Transactions on Information Systems10.1145/290371934:4(1-25)Online publication date: 9-Jun-2016
  • (2015)Discovering Topic Evolution Topology in a Microblog Corpus2015 Third International Conference on Advanced Cloud and Big Data10.1109/CBD.2015.12(7-14)Online publication date: Oct-2015
  • (2015)Social event identification and ranking on flickrWorld Wide Web10.1007/s11280-014-0295-z18:5(1219-1245)Online publication date: 1-Sep-2015
  • (2015)Mining streams of short text for analysis of world-wide event evolutionsWorld Wide Web10.1007/s11280-014-0293-118:5(1201-1217)Online publication date: 1-Sep-2015
  • (2014)ADI: Towards a Framework of App Developer InspectionDatabase Systems for Advanced Applications10.1007/978-3-319-05813-9_18(266-280)Online publication date: 2014
  • (2013)Spatio-temporal Event Modeling and RankingWeb Information Systems Engineering – WISE 201310.1007/978-3-642-41154-0_27(361-374)Online publication date: 2013
  • (2013)Beyond Click Graph: Topic Modeling for Search Engine Query Log AnalysisDatabase Systems for Advanced Applications10.1007/978-3-642-37487-6_18(209-223)Online publication date: 2013

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