Recommendation systems consist of methods for recommending products or any items that are of interest to users in web applications for personalized experience. The recommendation helps the users to reduce the time and complexity of searching for the required information. The recommendation methods use the information of users and items as well as users' past history of interaction to suggest preferred items. The context based methods use the situation about the user, item or interaction to give recommendations to users. Currently with the growth of techniques in acquiring the information of interaction of users with the system, the context based methods for recommendation improve the quality of recommendation. A brief review of the approaches and methods for context based recommendation is presented here with the challenges and future directions.

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Recommendation Systems Context Aware Pre And Post Filtering Contextual Model