Please use this identifier to cite or link to this item: http://hdl.handle.net/10216/43258
Author(s): Luís Sarmento
Sérgio Nunes
Jorge Teixeira
Eugénio Oliveira
Title: Propagating fine-grained topic labels in news snippets
Issue Date: 2009
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.
Subject: Inteligência artificial, Ciências da computação e da informação
Call Number: 57576
URI: http://hdl.handle.net/10216/43258
Source: 2009 IEEE/WIC/ACM INTERNATIONAL JOINT CONFERENCES ON WEB INTELLIGENCE (WI) AND INTELLIGENT AGENT TECHNOLOGIES (IAT), VOL 2
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: openAccess
License: https://creativecommons.org/licenses/by-nc/4.0/
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

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