TY - JOUR
T1 - A hybrid method for opinion finding task
T2 - 17th Text REtrieval Conference, TREC 2008
AU - Hoang, Linh
AU - Lee, Seung Wook
AU - Hong, Gumwon
AU - Lee, Joo Young
AU - Rim, Hae Chang
PY - 2008
Y1 - 2008
N2 - This paper presents an approach for the Opinion Finding task at TREC 2008 Blog Track. For the Ad-hoc Retrieval subtask, we adopt language model to retrieve relevant documents. For the Opinion Retrieval subtask, we propose a hybrid model of lexicon-based approach and machine learning approach for estimating and ranking the opinionated documents. For the Polarized Opinion Retrieval subtask, we employ machine learning for predicting the polarity and linear combination technique for ranking polar documents. The hybrid model which utilize both lexicon-based approach and machine learning approach to predict and rank opinionated documents are the focuses of our participation this year. Regarding the hybrid method for opinion retrieval subtask, our submitted runs yield 15% improvement over baseline.
AB - This paper presents an approach for the Opinion Finding task at TREC 2008 Blog Track. For the Ad-hoc Retrieval subtask, we adopt language model to retrieve relevant documents. For the Opinion Retrieval subtask, we propose a hybrid model of lexicon-based approach and machine learning approach for estimating and ranking the opinionated documents. For the Polarized Opinion Retrieval subtask, we employ machine learning for predicting the polarity and linear combination technique for ranking polar documents. The hybrid model which utilize both lexicon-based approach and machine learning approach to predict and rank opinionated documents are the focuses of our participation this year. Regarding the hybrid method for opinion retrieval subtask, our submitted runs yield 15% improvement over baseline.
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M3 - Conference article
AN - SCOPUS:84873466987
SN - 1048-776X
JO - NIST Special Publication
JF - NIST Special Publication
Y2 - 18 November 2008 through 21 November 2008
ER -