Recommender systems have become extremely common in recent years, and are applied in a variety of applications. The most popular ones are probably movies, music, news, books, research articles, search queries, social tags, and products in general. However, there are also recommender systems for experts, jokes, restaurants, financial services, life insurance, persons (online dating), and Twitter followers. In this paper, we present review of collaboration filtering for accurate web recommendation service using characteristics of QoS and user location and we use recommendation visualization map.

Service Recommendation, Collaboration Filtering, Visualization, QoS

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