Topic Extraction from Online Reviews for Classification and Recommendation
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|Title:||Topic Extraction from Online Reviews for Classification and Recommendation||Authors:||Dong, Ruihai
O'Mahony, Michael P.
|Permanent link:||http://hdl.handle.net/10197/8457||Date:||9-Aug-2013||Abstract:||Automatically identifying informative reviews is increasingly important given the rapid growth of user generated reviews on sites like Amazon and TripAdvisor. In this paper, we describe and evaluate techniques for identifying and recommending helpful product reviews using a combination of review features, including topical and sentiment information, mined from a review corpus.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||AAAI||Copyright (published version):||2013 AAAI||Keywords:||Recommender systems;Classification;Reviews||Language:||en||Status of Item:||Peer reviewed||Is part of:||Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI 13)||Conference Details:||Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI 13), Beijing, China, 3-9 August 2013|
|Appears in Collections:||CLARITY Research Collection|
Computer Science Research Collection
Insight Research Collection
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