The Reviewer's Assistant: Recommending Topics to Writers by Association Rule Mining and Case-base Reasoning

Title: The Reviewer's Assistant: Recommending Topics to Writers by Association Rule Mining and Case-base Reasoning
Authors: Dong, Ruihai
Schaal, Markus
O'Mahony, Michael P.
Smyth, Barry
Permanent link: http://hdl.handle.net/10197/4348
Date: 17-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. 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 extended abstract 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.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Keywords: Usage analysisUser-generated contentRecommender systemTopic extraction
Language: en
Status of Item: Not peer reviewed
Conference Details: The 23rd Irish Conference on Artificial Intelligence and Cognitive Science (AICS 2012), Dublin City University, Dublin, Ireland, 17-19 September, 2012
Appears in Collections:Computer Science Research Collection

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