Simple Semantics in Topic Detection and Tracking

[1]  James Allan,et al.  Extracting significant time varying features from text , 1999, CIKM '99.

[2]  Victor Lavrenko,et al.  Event Tracking , 1998 .

[3]  P. Falk.  The past to come , 1988 .

[4]  Mark Liberman,et al.  Corpora for topic detection and tracking , 2002 .

[5]  J. Michael Schultz,et al.  Towards a Universal dictionary for multi-language information retrieval applications , 2002 .

[6]  Duane Szafron,et al.  Temporal Granularity: Completing the Puzzle , 2004, Journal of Intelligent Information Systems.

[7]  Yiming Yang,et al.  Topic-conditioned novelty detection , 2002, KDD.

[8]  Thorsten Joachims,et al.  Learning to classify text using support vector machines - methods, theory and algorithms , 2002, The Kluwer international series in engineering and computer science.

[9]  Jonathan G. Fiscus,et al.  Topic detection and tracking evaluation overview , 2002 .

[10]  Helena Ahonen-Myka,et al.  Topic Detection and Tracking with Spatio-Temporal Evidence , 2003, ECIR.

[11]  James Allan,et al.  Topic detection and tracking: event-based information organization , 2002 .

[12]  Yiming Yang,et al.  A re-examination of text categorization methods , 1999, SIGIR '99.

[13]  James Allan,et al.  First story detection in TDT is hard , 2000, CIKM '00.

[14]  Philip A. Schrodt,et al.  MACHINE CODING OF EVENT DATA USING REGIONAL AND INTERNATIONAL SOURCES , 1994 .

[15]  Helena Ahonen-Myka,et al.  Applying Semantic Classes in Event Detection and Tracking , 2002 .

[16]  James Allan,et al.  Explorations within topic tracking and detection , 2002 .

[17]  George A. Miller,et al.  WordNet: A Lexical Database for English , 1995, HLT.

[18]  Fabrizio Sebastiani,et al.  Machine learning in automated text categorization , 2001, CSUR.

[19]  James Allan,et al.  Relevance models for topic detection and tracking , 2002 .

[20]  Roberto Basili,et al.  Learning to Classify Text Using Support Vector Machines: Methods, Theory, and Algorithms by Thorsten Joachims , 2003, Comput. Linguistics.

[21]  Jonathan Yamron,et al.  Statistical models of topical content , 2002 .

[22]  David R. Karger,et al.  Scatter/Gather: a cluster-based approach to browsing large document collections , 1992, SIGIR '92.

[23]  W. Bruce Croft,et al.  On-line new event detection, clustering, and tracking (information retrieval, internet) , 1999 .

[24]  Rafael Berlanga Llavori,et al.  Temporal-Semantic Clustering of Newspaper Articles for Event Detection , 2002, PRIS.

[25]  Yiming Yang,et al.  Learning approaches for detecting and tracking news events , 1999, IEEE Intell. Syst..

[26]  Yiming Yang,et al.  Topic Detection and Tracking Pilot Study Final Report , 1998 .

[27]  Tim Leek,et al.  Probabilistic approaches to topic detection and tracking , 2002 .

[28]  R. Papka,et al.  On-line new event detection and tracking , 1998, SIGIR '98.

[29]  R. Papka.  On-line New Event Detection, Clustering, and Tracking TITLE2: , 1999 .

[30]  Klaus Krippendorff,et al.  On the Reliability of Unitizing Continuous Data , 1995 .

[31]  Yiming Yang,et al.  Improving text categorization methods for event tracking , 2000, SIGIR '00.

[32]  Gerard Salton,et al.  Term-Weighting Approaches in Automatic Text Retrieval , 1988, Inf. Process. Manag..

[33]  Helena Ahonen-Myka,et al.  Utilizing Temporal Information in Topic Detection and Tracking , 2003, ECDL.

[34]  James Allan,et al.  Introduction to topic detection and tracking , 2002 .

[35]  M. Sherwood-Smith,et al.  Lexical chains for topic tracking , 2002, IEEE International Conference on Systems, Man and Cybernetics.