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.
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Amati, G., Ambrosi, E., Bianchi, M., Gaibisso, C., Gambosi, G. (2008). Automatic Construction of an Opinion-Term Vocabulary for Ad Hoc Retrieval. In: Macdonald, C., Ounis, I., Plachouras, V., Ruthven, I., White, R.W. (eds) Advances in Information Retrieval. ECIR 2008. Lecture Notes in Computer Science, vol 4956. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78646-7_11
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