KLE at TREC 2008 Blog Track: Blog Post and Feed Retrieval
POHANG UNIV OF SCIENCE AND TECHNOLOGY (SOUTH KOREA)
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This paper describes our participation in the TREC 2008 Blog Track. For the opinion task, we made an opinion retrieval model that consists of preprocessing, topic retrieval, opinion finding, and sentiment classification parts. For topic retrieval, our system is based on the passage-based retrieval model and feedback. For the opinion analysis, we created a PSEUDO OPINIONATED WORD POW, O, which is representative of all opinion words, and expanded the original query with O. For the blog distillation task, we integrated the average score of all posts within a feed, and the average score of the most relevant N post scores. We also examined the pseudo-relevance feedback for the distillation task by focusing on various document selection schemes to expand the query terms. The experimental results show a significant improvement over previous results.
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