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In everyday life one has to take a variety of decisions. So there is a need for recommendation which information may be relevant and which is rather unimportant to support decision making. Frequently we find recommendation systems to assist clients in online-shops and other internet environments. The objective of these systems is the implementation of user-friendly interfaces with a high degree of personalization and efficient decision support. This paper evaluates several machine-learningdoi:10.1109/hicss.2007.460 dblp:conf/hicss/FeldenC07 fatcat:dtjjk23uvfbdxb4kwq5maeahz4