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User activity measurement in rating-based online-to-offline (O2O) service recommendation
Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
Stockholm University, Faculty of Social Sciences, Stockholm Business School.
Number of Authors: 42019 (English)In: Information Sciences, ISSN 0020-0255, E-ISSN 1872-6291, Vol. 479, p. 180-196Article in journal (Refereed) Published
Abstract [en]

The increasing popularity of O2O service make more and more people begin seeking and booking services online. After that, they experience the services in brick-and-mortar stores. This new business model has marketing potential and offer various opportunities to different industries. Consequently, various O2O services starting to appear, which results in difficult service selections for customers. Therefore, in this paper, we proposed a novel rating-based O2O service recommendation model considering user activity. In this method, the traditional similarity estimations are substituted by user activity which can better reflect the differentiations of customers' behavioral characteristics. Therefore, recommendations are more accurate. The experimental results show that proposed method outperforms rating-based methods, including widely used collaborative filtering methods and state-of-the-art matrix methods. In addition, we find the optimal parameter values of our model, and explore the influence of Top-k on rating-based recommendation.

Place, publisher, year, edition, pages
2019. Vol. 479, p. 180-196
Keywords [en]
O2O service, User activity, Collaborative filtering, Rating-based recommendation
National Category
Economics and Business
Identifiers
URN: urn:nbn:se:su:diva-166656DOI: 10.1016/j.ins.2018.11.009ISI: 000458229200011OAI: oai:DiVA.org:su-166656DiVA, id: diva2:1294398
Available from: 2019-03-07 Created: 2019-03-07 Last updated: 2019-03-07Bibliographically approved

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