Leveraging product adopter information from online reviews for product recommendation

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Abstract

The availability of the sheer volume of online product reviews makes it possible to derive implicit demographic information of product adopters from review documents. This paper proposes a novel approach to the extraction of product adopter mentions from online reviews. The extracted product adopters are the ncategorise into a number of different demographic user groups. The aggregated demographic information of many product adopters can be used to characterize both products and users, which can be incorporated into a recommendation method using weighted regularised matrix factorisation. Our experimental results on over 15 million reviews crawled from JINGDONG, the largest B2C e-commerce website in China, show the feasibility and effectiveness of our proposed frame work for product recommendation.

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Publication dateJul 2015
Publication titleProceedings of the 9th International Conference on Web and Social Media
EditorsDaniele Quercia, Bernie Hogan
PublisherAAAI
Pages464-472
Number of pages9
ISBN (Print)978-1-57735-733-9
Original languageEnglish
Event9th International Conference on Web and Social Media - Oxford, United Kingdom

Conference

Conference9th International Conference on Web and Social Media
Abbreviated titleICWSM 2015
CountryUnited Kingdom
CityOxford
Period26/05/1529/05/15

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