Recommender Systems are eminently in demand to manage the problem of highly overloading data and to avoid the retrieval of irrelevant information from Web, which is a major part of Information Filtering. Recommender Systems helps user to make precise and explicit decisions and study the user�s knowledge to enhance the Business growth. Different Recommendation methods are implemented for achieving varied recommendations in numerous vital applications based on the expected behavior of the system and relevant data mining strategies are used to perform efficient information retrieval. This paper analyses the various Recommendation methods available for building effective Recommender Systems and exploits the participation and usage of Recommendation methods in different domains. This paper also focuses to discuss Data Mining techniques and their scope towards implementing such effective Recommender Systems.

Recommendation Algorithm; Content Based Filtering; Collaborative Filtering; Hybrid Recommendation; Knowledge Based Recommendation; Group Recommendation; Data Mining Methods

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