We investigate the effectiveness of both the standard evaluation measures and the opinion component for topical opinion retrieval. We analyze how relevance is affected by opinions by perturbing relevance ranking by the outcomes of opinion-only classiffiers built by Monte Carlo sampling. Topical opinion rankings are obtained by either re-ranking or filtering the documents of a rst-pass retrieval of topic relevance. The proposed approach establishes the correlation between the accuracy and the precision of the classier and the performance of the topical opinion retrieval. Among other results, it is possible to assess the effectiveness of the opinion component by comparing the eectiveness of the relevance baseline with the topical opinion ranking
On performance of Topical Opinion Retrieval
Carlo Gaibisso;
2010
Abstract
We investigate the effectiveness of both the standard evaluation measures and the opinion component for topical opinion retrieval. We analyze how relevance is affected by opinions by perturbing relevance ranking by the outcomes of opinion-only classiffiers built by Monte Carlo sampling. Topical opinion rankings are obtained by either re-ranking or filtering the documents of a rst-pass retrieval of topic relevance. The proposed approach establishes the correlation between the accuracy and the precision of the classier and the performance of the topical opinion retrieval. Among other results, it is possible to assess the effectiveness of the opinion component by comparing the eectiveness of the relevance baseline with the topical opinion rankingI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
