Last decade and half had been witnessed to an unprecedented expansion of Internet. This has resulted in data overloading; due to which it has become an increasing problem for retrieving useful information from internet. Users searching for products or content have endless number of Web pages to navigate and require enormous efforts, requires judgmental aptitude and intuitiveness to extract meaningful information from the enormous data. Recommender systems are meant to be an important solution

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... the data overload and skewed information problem that persists today in World Wide Web. The job of the recommender system is to provide the consumer with a selection of products or content which suit his/her needs so that the user need not browse through enormous number of web pages. Recommender system has undergone a lot of improvements in last two decades in terms of accuracy in output and has been an intense area of research in recent times. This paper discusses the various improvements in the field of recommender system from the past to the present and also explores the future research trends.