We present a method to automatically generate a term-opinion lexicon. We also weight these lexicon terms and use them at real time to boost the ranking with opinionated-content documents. We define very simple models both for opinion-term extraction and document ranking. Both the lexicon model and retrieval model are assessed. To evaluate the quality of the lexicon we compare performance with a well-established manually generated opinion-term dictionary. We evaluate the effectiveness of the term-opinion lexicon using the opinion task evaluation data of the TREC 2007 blog track.

Automatic construction of an opinion-term vocabulary for ad hoc retrieval

Edgardo Ambrosi;Carlo Gaibisso;
2008

Abstract

We present a method to automatically generate a term-opinion lexicon. We also weight these lexicon terms and use them at real time to boost the ranking with opinionated-content documents. We define very simple models both for opinion-term extraction and document ranking. Both the lexicon model and retrieval model are assessed. To evaluate the quality of the lexicon we compare performance with a well-established manually generated opinion-term dictionary. We evaluate the effectiveness of the term-opinion lexicon using the opinion task evaluation data of the TREC 2007 blog track.
2008
Istituto di Analisi dei Sistemi ed Informatica ''Antonio Ruberti'' - IASI
ASR - Unità Reti e Sistemi
Inglese
Macdonald, C., Ounis, I., Plachouras, V., Ruthven, I., White, R.W. (eds)
Advances in Information Retrieval. ECIR 2008
30th European Conference on IR Research, ECIR 2008
4956
89
100
12
Springer
Berlin, Heidelberg
GERMANIA
Sì, ma tipo non specificato
March 30-April 3, 2008
Glasgow
Information Retrieval
sentiment analisys
5
restricted
Amati, Giambattista; Ambrosi, Edgardo; Bianchi, Marco; Gaibisso, Carlo; Gambosi, Giorgio
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/170272
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