Harnessing the Experience Web to Support User-Generated Product Reviews

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Title: Harnessing the Experience Web to Support User-Generated Product Reviews
Authors: Dong, Ruihai
Schaal, Markus
O'Mahony, Michael P.
McCarthy, Kevin
Smyth, Barry
Permanent link: http://hdl.handle.net/10197/4343
Date: 3-Sep-2012
Abstract: Today, online reviews for products and services have become an important class of user-generated content and they play a valuable role for countless online businesses by helping to convert casual browsers into informed and satisfied buyers. In many respects, the content of user reviews is every bit as important as the catalog content that describes a given product or service. As users gravitate towards sites that offer insightful and objective reviews, the ability to source helpful reviews from a community of users is increasingly important. In this work we describe the Reviewer’s Assistant, a case-based reasoning inspired recommender system designed to help people to write more helpful reviews on sites such as Amazon and TripAdvisor. In particular, we describe two approaches to helping users during the review writing process and evaluate each as part of a blind live-user study. Our results point to high levels of user satisfaction and improved review quality compared to a control-set of Amazon reviews.
Type of material: Conference Publication
Publisher: Springer
Copyright (published version): 2012 Springer-Verlag Berlin Heidelberg
Keywords: Association ruleOnline reviewProduct reviewTopic extractionOnline customer review
DOI: 10.1007/978-3-642-32986-9_7
Language: en
Status of Item: Not peer reviewed
Is part of: Díaz Agudo, Belén; Watson, Ian. (eds.). Case-Based Reasoning Research and Development (Lecture Notes in Computer Science, Volume 7466)
Conference Details: Proceedings of the 20th International Conference, ICCBR 2012, Lyon, France, September 3-6, 2012.
Appears in Collections:Computer Science Research Collection

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