Topic Detection and Tracking interface with named entities approach

Topic Detection and Tracking (TDT) refer to the technologies and techniques in analysing and handling the vast amount of information arriving continuously from the news stream. Some issues in news monitoring regarding interface design are considered. In this paper we present the techniques and works done in TDT domain. We discuss the named entities approach used in document representation and in user interface. Finally, we present the suggested approach to improve users' performance and to facilitate them to perform an effective TDT task.

[1]  James Allan,et al.  Text classification and named entities for new event detection , 2004, SIGIR '04.

[2]  Gareth J. F. Jones,et al.  A visualisation tool for topic tracking analysis and development , 2002, SIGIR '02.

[3]  Chengzhi Zhang,et al.  Automatic Keyword Extraction from Documents Using Conditional Random Fields , 2008 .

[4]  Helena Ahonen-Myka,et al.  Simple Semantics in Topic Detection and Tracking , 2004, Information Retrieval.

[5]  Hitoshi Isahara,et al.  IREX: IR & IE Evaluation Project in Japanese , 2000, LREC.

[6]  James Allan,et al.  Automatic generation of overview timelines , 2000, SIGIR '00.

[7]  James Allan,et al.  Taking Topic Detection From Evaluation to Practice , 2005, Proceedings of the 38th Annual Hawaii International Conference on System Sciences.

[8]  Hal Berghel,et al.  Cyberspace 2000: dealing with information overload , 1997, CACM.

[9]  Ramayya Krishnan,et al.  Incremental hierarchical clustering of text documents , 2006, CIKM '06.

[10]  Wei Zheng,et al.  Topic Tracking Based on Keywords Dependency Profile , 2008, AIRS.

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

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

[13]  James Allan,et al.  On-Line New Event Detection and Tracking , 1998, SIGIR.

[14]  Fabio Crestani,et al.  Evaluation of an interactive topic detection and tracking interface , 2012, J. Inf. Sci..

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

[16]  Hila Becker,et al.  Event Identification in Social Media , 2009, WebDB.

[17]  Bettina Berendt,et al.  STORIES in Time: A Graph-Based Interface for News Tracking and Discovery , 2009, 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology.

[18]  Ralph Grishman,et al.  Message Understanding Conference- 6: A Brief History , 1996, COLING.

[19]  J. Teevan The ReSearch Engine : Helping People Return to Information in Dynamic Information Environments , 2022 .

[20]  James Allan,et al.  Lighthouse: showing the way to relevant information , 2000, IEEE Symposium on Information Visualization 2000. INFOVIS 2000. Proceedings.

[21]  Shahrul Azman Mohd. Noah,et al.  Going Beyond the Surrounding Text to Semantically Annotate and Search Digital Images , 2010, ACIIDS.

[22]  Kuo Zhang,et al.  New event detection based on indexing-tree and named entity , 2007, SIGIR.