document: Opinion integration through semi-supervised topic modeling Web 2.0 technology has enabled more and more people to freely express their opinions on the Web , making the Web an extremely valuable source for mining user opinions about all kinds of topics . In this paper we study how to automatically integrate opinions expressed in a well-written expert review with lots of opinions scattering in various sources such as blogspaces and forums . We formally define this new integration problem and propose to use semi-supervised topic models to solve the problem in a principled way . Experiments on integrating opinions about two quite different topics ( a product and a political figure ) show that the proposed method is effective for both topics and can generate useful aligned integrated opinion summaries . The proposed method is quite general . It can be used to integrate a well written review with opinions in an arbitrary text collection about any topic to potentially support many interesting applications in multiple domains .
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