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Shi, Y., Larson, M. and Hanjalic, A. (2011) Tags as Bridges between Domains: Improving Recommendation with Tag- Induced Cross-Domain Collaborative Filtering. User Modeling, Adaption & Personalization-international Conference, 6787, 305-316.

has been cited by the following article:

• TITLE: Research on the Personalized Recommendation Algorithm for Hairdressers

  AUTHORS: Zhixin Liang, Fengying Wang

  KEYWORDS: Recommender System, The Nearest Neighbor Recommendation, Classify, Logistic Regression

  JOURNAL NAME: Open Journal of Modelling and Simulation, Vol.4 No.3, July 1, 2016

  ABSTRACT: In order to retain customers, hairdressers usually persuade customers to be their members by offering membership card. This paper studies how to set up their recommendation system in the hairdressers. According to the membership information and consumer behavior, the hairdresser provides personalized recommendation to different members and lets customers experience personalized choices. A recommendation algorithm based on customer ratings and a customer classification method based on Logistic Regression Model are discussed in this paper. The former is used to recommend hair style and color to a customer. The latter is used to determine whether to recommend some maintenance programs to a customer or not.