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In the era of Web 2.0, huge volumes of consumer reviews are posted to the Internet every day. Manual approaches to detecting and analyzing fake reviews (i.e., spam) are not practical due to the problem of information overload. However, the design and development of automated methods of detecting fake reviews is a challenging research problem. The main(More)
This paper presents the CUHK opinion analysis system, namely Opinmine, for the NTCIR-6 pilot task. Opinmine comprises of three functional modules: (1) Preprocessing and Assignment Module (PAM) performs word segmentation, part-of-speech (POS) tagging and named entity recognition on the input Chinese text. It is based on lexicalized Hidden Markov Model and(More)
Understanding intent underlying search query recently attracted enormous research interests. Two challenging issues are worth noting: First, words within query are usually ambiguous while query in most cases is too short to disambiguate. Second, ambiguity in some cases cannot be resolved according merely to the limited query context. It is thus demanded(More)