Proximity-based opinion retrieval

Blog post opinion retrieval aims at finding blog posts that are relevant and opinionated about a user’s query. In this paper we propose a simple probabilistic model for assigning relevant opinion scores to documents. The key problem is how to capture opinion expressions in the document, that are related to the query topic. Current solutions enrich general opinion lexicons by finding query-specific opinion lexicons using pseudo-relevance feedback on external corpora or the collection itself. In this paper we use a general opinion lexicon and propose using proximity information in order to capture opinion term relatedness to the query. We propose a proximity-based opinion propagation method to calculate the opinion density at each point in a document. The opinion density at the position of a query term in the document can then be considered as the probability of opinion about the query term at that position. The effect of different kernels for capturing the proximity is also disc...

• Type: Conference
• Year: 2010
• Where: SIGIR
• Authors: Shima Gerani, Mark James Carman, Fabio Crestani
• Keywords: General Opinion Lexicon, Information Management, Opinion Density, Opinion Lexicon, SIGIR 2010