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
Schaal, Markus
O'Mahony, Michael P.
Smyth, Barry
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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