Propagating Fine-Grained Topic Labels in News Snippets

Authors:
Luis Sarmento;Sérgio Nunes;Jorge Teixeira;Eugénio Oliveira
Affiliations:
-;-;-;-
Venue:
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Year:
2009

Citing 5
Cited 0

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Abstract

We propose an unsupervised method for propagating automatically extracted fine-grained topic labels among news items to improve their topic description for subsequent text classification procedure. This method compares vector representations of news items and assigns to each news item the label of its closest neighbour with a different topic label. Results obtained show that high precision can be achieved in propagating the top ranked topic label, and that 2-gram and 3-gram feature representations optimize the precision.