A Tripartite-Graph Based Recommendation Framework for Price-Comparison Services
- Title
- A Tripartite-Graph Based Recommendation Framework for Price-Comparison Services
- Author
- 김상욱
- Keywords
- recommendation systems; price-comparison services; random walk with restart
- Issue Date
- 2019-06
- Publisher
- COMSIS CONSORTIUM
- Citation
- COMPUTER SCIENCE AND INFORMATION SYSTEMS, v. 16, no. 2, Page. 333-357
- Abstract
- The recommender systems help users who are going through numerous items (e.g., movies or music) presented in online shops by capturing each user's preferences on items and suggesting a set of personalized items that s/he is likely to prefer [8]. They have been extensively studied in the academic society and widely utilized in many online shops [33]. However, to the best of our knowledge, recommending items to users in price-comparison services has not been studied extensively yet, which could attract a great deal of attention from shoppers these days due to its capability to save users' time who want to purchase items with the lowest price [31]. In this paper, we examine why existing recommendation methods cannot be directly applied to price-comparison services, and propose three recommendation strategies that are tailored to price-comparison services: (1) using click-log data to identify users' preferences, (2) grouping similar items together as a user's area of interest, and (3) exploiting the category hierarchy and keyword information of items. We implement these strategies into a unified recommendation framework based on a tripartite graph. Through our extensive experiments using real-world data obtained from Naver shopping, one of the largest price-comparison services in Korea, the proposed framework improved recommendation accuracy up to 87% in terms of precision and 129% in terms of recall, compared to the most competitive baseline.
- URI
- http://www.doiserbia.nb.rs/Article.aspx?ID=1820-02141900005L#.XsHhq2gzaUkhttps://repository.hanyang.ac.kr/handle/20.500.11754/151937
- ISSN
- 1820-0214
- DOI
- 10.2298/CSIS181012005L
- Appears in Collections:
- COLLEGE OF ENGINEERING[S](공과대학) > COMPUTER SCIENCE(컴퓨터소프트웨어학부) > Articles
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