2012 International Conference on Cloud and Service Computing (2012)
Shanghai, China China
Nov. 22, 2012 to Nov. 24, 2012
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSC.2012.30
Rong Hu , State Key Lab. for Novel Software Technol., Nanjing Univ., Nanjing, China
Wanchun Dou , State Key Lab. for Novel Software Technol., Nanjing Univ., Nanjing, China
Jianxun Liu , Key Lab. of Knowledge Process. & Networked Manuf., Hunan Univ. of Sci & Tec, Xiangtan, China
It is a challenge to recommend Web services under multiple contexts. To address this challenge, we propose a context-aware collaborative filtering (CaCF) approach for service recommendation. Three types of contextual information, i.e. time, location and interest of user, are considered. In this approach, users' interests are extracted from service invocation records and represented as term-weight vectors. Neighbors are chosen according to the Cosine similarities of these vectors. Then, neighbors are filtered into close neighbors by location and time. At last, these close neighbors recommend service to a target user. We evaluate our method through comparing with other service recommendation approaches. The experimental results show that it achieves better precision and satisfaction rate than other two methods.
ubiquitous computing, collaborative filtering, recommender systems, cosine similarities, Web services, context-aware collaborative filtering approach, service recommendation, contextual information, service invocation records, term-weight vectors, Context, IP networks, Recommender systems, Collaboration, Web services, Vectors, time, collaborative filtering, context-aware, service recommendation, location
Rong Hu, Wanchun Dou and Jianxun Liu, "A context-aware collaborative filtering approach for service recommendation," 2012 International Conference on Cloud and Service Computing(CSC), Shanghai, China China, 2012, pp. 148-155.