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Recommendation generation is a critical need in today's time. With the advent of big data and the increasing number of users, generation of most suitable recommendation is essential. There are many issues already associated with recommendations such as data acquisition, scalability, etc.. Moreover, the users today look to get best recommendations at the minimum effort on their side. Thus it becomes difficult to manage such huge amount of information, extract the needed data and present it to the user with least user involvement. In this research, we surveyed some recommendation algorithms and analyze their applications on an open cloud server which uses linked data to generate automated recommendations.