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.
| Original language | English |
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| Title of host publication | Proceedings of the 9th International Conference on Web and Social Media |
| Editors | Daniele Quercia, Bernie Hogan |
| Publisher | AAAI |
| Pages | 464-472 |
| Number of pages | 9 |
| ISBN (Print) | 978-1-57735-733-9 |
| Publication status | Published - Jul 2015 |
| Event | 9th International Conference on Web and Social Media - Oxford, United Kingdom Duration: 26 May 2015 → 29 May 2015 |
Conference
| Conference | 9th International Conference on Web and Social Media |
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| Abbreviated title | ICWSM 2015 |
| Country/Territory | United Kingdom |
| City | Oxford |
| Period | 26/05/15 → 29/05/15 |