Please use this identifier to cite or link to this item:
https://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 Artificial intelligence, Computer and information sciences |
| Scientific areas: | Ciências exactas e naturais::Ciências da computação e da informação Natural sciences::Computer and information sciences |
| DOI: | 10.1109/wi-iat.2009.338 |
| URI: | https://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 |
This item is licensed under a Creative Commons License
