document: Sentence-level contextual opinion retrieval Existing opinion retrieval techniques do not provide context-dependent relevant results . Most of the approaches used by state-of-the-art techniques are based on frequency of query terms , such that all documents containing query terms are retrieved , regardless of contextual relevance to the intent of the human seeking the opinion . However , in a particular opinionated document , words could occur in different contexts , yet meet the frequency attached to a certain opinion threshold , thus explicitly creating a bias in overall opinion retrieved . In this paper we propose a sentence-level contextual model for opinion retrieval using grammatical tree derivations and approval voting mechanism . Model evaluation performed between our contextual model , BM25 , and language model shows that the model can be effective for contextual opinion retrieval such as faceted opinion retrieval .
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