A hybrid method for opinion finding task: KUNLP at TREC 2008 blog track

Linh Hoang, Seung Wook Lee, Gumwon Hong, Joo Young Lee, Hae-Chang Rim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationNIST Special Publication
Publication statusPublished - 2008
Event17th Text REtrieval Conference, TREC 2008 - Gaithersburg, MD, United States
Duration: 2008 Nov 182008 Nov 21

Other

Other17th Text REtrieval Conference, TREC 2008
CountryUnited States
CityGaithersburg, MD
Period08/11/1808/11/21

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Hoang, L., Lee, S. W., Hong, G., Lee, J. Y., & Rim, H-C. (2008). A hybrid method for opinion finding task: KUNLP at TREC 2008 blog track. In NIST Special Publication