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Sidan uppdaterades: 2012-09-11 15:12
| Författare |
Qi Ju Richard Johansson Alessandro Moschitti |
|---|---|
| Publicerad i | Proceedings of the Joint ECML/PKDD-PASCAL Workshop on Large-Scale Hierarchical Classification; September 5, 2011; Athens, Greece |
| Publiceringsår | 2011 |
| Publicerad vid |
Institutionen för svenska språket |
| Språk | en |
| Ämnesord | datorlingvistik, språkteknologi, textkategorisering, maskininlärning |
| Ämneskategorier | Språkteknologi (språkvetenskaplig databehandling), Övrig informationsteknik |
We consider the use of reranking as a way to relax typical in- dependence assumptions often made in hierarchical multilabel classification. Our reranker is based on (i) an algorithm that generates promising k-best classification hypotheses from the output of local binary classifiers that clas- sify nodes of a target tree-shaped hierarchy; and (ii) a tree kernel-based reranker applied to the classification tree associated with the hypotheses above. We carried out a number of experiments with this model on the Reuters corpus: we firstly show the potential of our algorithm by computing the oracle classification accuracy. This demonstrates that there is a signifi- cant room for potential improvement of the hierarchical classifier. Then, we measured the accuracy achieved by the reranker, which shows a significant performance improvement over the baseline.
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