In this paper, we encode topic dependencies in hierarchical multi-label Text Categoriza- tion (TC) by means of rerankers. We rep- resent reranking hypotheses with several in- novative kernels considering both the struc- ture of the hierarchy and the probability of nodes. Additionally, to better investigate the role of category relationships, we consider two interesting cases: (i) traditional schemes in which node-fathers include all the documents of their child-categories; and (ii) more gen- eral schemes, in which children can include documents not belonging to their fathers. The extensive experimentation on Reuters Corpus Volume 1 shows that our rerankers inject ef- fective structural semantic dependencies in multi-classifiers and significantly outperform the state-of-the-art.
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Titolo: | Modeling Topic Dependencies in Hierarchical Text Categorization |
Autori: | A. Moschitti; Q. Ju; R. Johansson |
Autori Unitn: | |
Titolo del volume contenente il saggio: | Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) |
Luogo di edizione: | Jeju Island, Korea |
Casa editrice: | The Association for Computer Linguistics |
Anno di pubblicazione: | 2012 |
Codice identificativo Scopus: | 2-s2.0-84878213949 |
Handle: | http://hdl.handle.net/11572/95263 |
Appare nelle tipologie: | 04.1 Saggio in atti di convegno (Paper in proceedings) |