A study on the evaluation of opinion retrieval systems (Contributo in atti di convegno)

Type
Label
  • A study on the evaluation of opinion retrieval systems (Contributo in atti di convegno) (literal)
Anno
  • 2010-01-01T00:00:00+01:00 (literal)
Alternative label
  • Giambattista Amati; Giuseppe Amodeo; Valerio Capozio; Carlo Gaibisso; Giorgio Gambosi; (2010)
    A study on the evaluation of opinion retrieval systems
    in First Italian Information Retrieval Workshop, Padova, Italy, january 27-28
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Giambattista Amati; Giuseppe Amodeo; Valerio Capozio; Carlo Gaibisso; Giorgio Gambosi; (literal)
Pagina inizio
  • 47 (literal)
Pagina fine
  • 51 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • IIR 2010 - Proceedings of the First Italian Information Retrieval Workshop (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#volumeInCollana
  • 560 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • Italian Information Retrieval Workshop (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 5 (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • Giambattista Amati: Fondazione Ugo Bordoni, Rome, Italy Giuseppe Amodeo: Dept. of Computer Science, University of L'Aquila, L'Aquila, Italy Valerio Capozio: Dept. of Mathematics, University of Rome \"Tor Vergata\", Rome, Italy Carlo Gaibisso: Istituto di Analisi dei Sistemi ed Informatica \"Antonio Ruberti\" - CNR, Rome, Italy Giorgio Gambosi: Dept. of Mathematics, University of Rome \"Tor Vergata\" Rome, Italy (literal)
Titolo
  • A study on the evaluation of opinion retrieval systems (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume
  • Massimo Melucci; Stefano Mizzaro; Gabriella Pasi (literal)
Abstract
  • We study the evaluation of opinion retrieval systems. Opinion retrieval is a relatively new research area, nevertheless classical evaluation measures, those adopted for ad hoc retrieval, such as MAP, precision at 10 etc., were used to assess the quality of rankings. In this paper we investigate the effectiveness of these standard evaluation measures for topical opinion retrieval. In doing this we split the opinion dimension from the relevance one and use opinion classffiers, with varying accuracy, to analyse how opinion retrieval performance changes by perturbing the outcomes of the opinion classiffiers. Classiffiers could be studied in two modalities, that is either to re-rank or to filter out directly documents obtained through a first relevance retrieval. In this paper we formally outline both approaches, while for now focussing on the filtering process. The proposed approach aims to establish the correlation between the accuracy of the classiffiers and the performance of the topical opinion retrieval. In this way it will be possible to assess the effectiveness of the opinion component by comparing the effectiveness of the relevance baseline with that of the topical opinion. (literal)
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