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With the rapid growth in multimedia services and the enormous offers of video contents in online social networks, users have difficulty in obtaining their interests. Therefore, various personalized recommendation systems have been proposed. In addition, none of them has considered both the privacy of users' contexts (e,g., social status, ages and hobbies) and video service vendors' repositories, which are extremely sensitive and of significant commercial value. To handle these problems, it's been proposed a cloud-assisted differentially private video recommendation system based on distributed online learning.In our project we proposed the new optimization technique for recommendation. The video recommendation is based on user's behavior (user's interest) and also using the pattern mining for video tag search recommendation. We have search option as sub category search and global search in our application. Facing massive multimedia services and contents in the Internet is based the content provider. In that group of providers we need to find out the irrelevant content promoters. Content promoters are usually trying to promote their contents to social media service or video service sites in internet. In our project Based on the user's interest we can detect and avoid the irrelevant content and content promoters.

Big data computing in clouds is a new paradigm for next-generation analytics development. It enables large-scale data organizations to share and explore large quantities of ever-increasing data types using cloud computing technology as a back-end. Knowledge exploration and decision-making from this rapidly increasing volume of data encourage data organization, access, and timely processing, an evolving trend known as big data computing. This modern paradigm incorporates large-scale computing, new data-intensive techniques, and mathematical models to create data analytics for intrinsic information extraction. Cloud computing emerged as a service-oriented computing model to deliver infrastructure, platform, and applications as services from the providers to the consumers meeting the QoS parameters by enabling the archival and processing of large volumes of rapidly growing data faster economy models.