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.
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