DocumentCode :
389470
Title :
Lexical chains for topic tracking
Author :
Carthy, Joe ; Sherwood-Smith, Michael
Author_Institution :
Dept. of Comput. Sci., Univ. Coll. Dublin, Ireland
Volume :
7
fYear :
2002
fDate :
6-9 Oct. 2002
Abstract :
Describes research into the use of lexical chains to build effective topic tracking systems. Lexical chaining is a method of grouping lexically related terms into so called lexical chains, using simple natural language processing techniques. Topic tracking involves tracking a given news event in a stream of news stories i.e. finding all subsequent storks in the news stream that discuss the given event. It has grown out of the Topic Detection and Tracking (TDT) initiative sponsored by DARPA. The paper describes the results of a topic tracking system, LexTrack, based on lexical chaining and compares it to a tracking system designed using traditional IR techniques.
Keywords :
information retrieval; natural languages; text analysis; DARPA; LexTrack; Topic Detection and Tracking initiative; lexical chaining; lexical chains; lexically related terms; natural language processing; news event; topic tracking; Broadcasting; Computer crime; Design for manufacture; Earthquakes; Explosions; Peak to average power ratio; Sliding mode control; Target tracking; Testing; Vocabulary;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2002 IEEE International Conference on
ISSN :
1062-922X
Print_ISBN :
0-7803-7437-1
Type :
conf
DOI :
10.1109/ICSMC.2002.1175725
Filename :
1175725
Link To Document :
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