Facet-based opinion retrieval from blogs

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Facet-based opinion retrieval from blogs
Authors: Olga Vechtomova
Citation: Information Processing and Management 46 (1): 71-88. 2010
Database(s): Google Scholar cites
DOI: 10.1016/j.ipm.2009.06.005.
Link(s): http://dx.doi.org/10.1016/j.ipm.2009.06.005
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Facet-based opinion retrieval from blogs describes a information retrieval system with query expansion combined with elements from sentiment analysis for "opinion-based re-ranking".

Wikipedia is used for query expansion

Contents

[edit] Data

[edit] Method

[edit] Query expansion

The method for identifying "concepts" (a keyword/keyphrase/named entity) using Wikipedia was similar to the method described in Improving complex interactive question answering with Wikipedia anchor text. The query (first the entire part then subphrases) is matched with Wikipedia article titles. Query expansion is based on the redirects of Wikipedia. An example is given in Table 3.

Okapi BM25 in Wumpus.

[edit] Opinion-based re-ranking

"opinion-based re-ranking consists of adjusting the tf weights of query terms on the basis of their cooccurrence with subjective lexical units in fixed-size windows centered on the query term occurrences."

[edit] Results

Results for query expansion for the 3 blog corpus are given in Table 2.

[edit] Related papers

  1. Improving complex interactive question answering with Wikipedia anchor text
  2. UIC at TREC 208 blog track
  3. WIDIT in TREC 2008 blog track: Leveraging multiple sources of opinion evidence
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