NDLI: Simple Semantics in Topic Detection and Tracking

Content Provider	Springer Nature Link
Author	Makkonen, Juha Ahonen Myka, Helena Salmenkivi, Marko
Copyright Year	2004
Abstract	Topic Detection and Tracking (TDT) is a research initiative that aims at techniques to organize news documents in terms of news events. We propose a method that incorporates simple semantics into TDT by splitting the term space into groups of terms that have the meaning of the same type. Such a group can be associated with an external ontology. This ontology is used to determine the similarity of two terms in the given group. We extract proper names, locations, temporal expressions and normal terms into distinct sub-vectors of the document representation. Measuring the similarity of two documents is conducted by comparing a pair of their corresponding sub-vectors at a time. We use a simple perceptron to optimize the relative emphasis of each semantic class in the tracking and detection decisions. The results suggest that the spatial and the temporal similarity measures need to be improved. Especially the vagueness of spatial and temporal terms needs to be addressed.
Starting Page	347
Ending Page	368
Page Count	22
File Format	PDF
ISSN	13864564
Journal	Information Retrieval
Volume Number	7
Issue Number	3-4
e-ISSN	15737659
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2004-01-01
Publisher Place	Boston
Access Restriction	Subscribed
Subject Keyword	Data Structures, Cryptology and Information Theory Management of Computing and Information Systems
Content Type	Text
Resource Type	Article
Subject	Library and Information Sciences Information Systems

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