Notice of Violation of IEEE Publication PrinciplesHybrid recommender systems: Survey and experiments

Notice of Violation of IEEE Publication Principles

"Hybrid Recommender Systems: Survey and Experiments"
by Vipul Vekariya and G.R. Kulkarni
in Proceedings of the 2012 Digital Information and Communication Technology and it\´s Applications (DICTAP), 2012, pp. 469-473

After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE\´s Publication Principles.

This paper contains large portions of text from the paper cited below. The text and figures were copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.

"Hybrid Recommender Systems: Survey and Experiments"
by Robin Burke
in User Modeling and User-Adapted Interaction, Volume 12 Issue 4, November 2002, pp. 331-370

Recommender systems represent user preferences for the purpose of suggesting items to purchase or examine. They have become fundamental applications in electronic commerce and information access, providing suggestions that effectively prune large information spaces so that users are directed toward those items that best meet their needs and preferences. A variety of techniques have been proposed for performing recommendation, including content-based, collaborative, knowledge-based and other techniques. To improve performance, these methods have sometimes been combined in hybrid recommenders. This paper surveys the landscape of actual and possible hybrid recommenders, and introduces a novel hybrid, system that combines content-based recommendation and collaborative filtering to recommend restaurants.