IDL - International Digital Library Of Technology & Research Volume 1, Issue 6, June 2017
Available at: www.dbpublications.org
International e-Journal For Technology And Research-2017
HADOOP based Recommendation Algorithm for Micro-video URL Revathy Ramakrishnan Department of CSE, CMRIT, VTU Bengaluru, India revathyr1@gmail.com
Abstract:
In the recent years usage social media applications pervade in our daily life which makes the Social Networking Sites (SNSs) being dependent on users for content generation. Considering user interest, contents produced by individual SNSs significantly leaves some of the interest based content undiscovered. This led to facilitate features such as “like”, “share”, “hashtags” functions to deliver the content from one platform to another platform. These allowed users to interact with multiple SNSs but limited to receive contents for separate SNSs. Although Open Identity allowed users for single signin in multiple platforms, it still remained to target multiple platforms. A Unified Access Model is proposed to internet-based-content modeling where the content for the users could be images or videos or text. Videos of short length termed as “micro-videos” are more popular both for the viewers and also the producers. The work carried out provides a recommendation algorithm for micro-video url, which compared to traditional recommendation algorithms such as content based recommendation, the big data uses parallel computing framework. High performance computing is achieved by using slope one algorithm that uses Mapreduce and Hadoop techniques. Hence, the proposed recommendation system for micro-video url can achieve high performance parallel computing, which can be used by the producers and viewers. Keywords: Networking Sites; Hadoop; Mapreduce; parallel computing; Slope one; micro-video
IDL - International Digital Library
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INTRODUCTION
With an increase in the amount of data provided by social networks, Internet searches, etc., there was a need to revolutionize the data. "Big Data" describes a universe of very large dataset. Although, Big Data refers to the volume of data, it also signifies the important capabilities which involve processing of Big Data. Typically, a wide range of media and ecommerce firms such as news websites, video providers and also social networking websites, provide data (hereafter referred as "content") on the Internet and their primary goal is to generate revenue. Not only, Content providers tend to maximize their revenue through advertisements and subscriptions but also try to reduce the cost of content distribution. Hence the providers distribute their contents across several geographical locations and also to improve and understand user experience, special analytical services would be used (eg., Google Analytics). Social media applications that deliver contents are completely dependent on the Users and hence make them deliver the best possible quality with minimum cost. At the same time, Content providers will now have the ability to collect, store and analyze behavioral patterns from Users. Users are proactively engaged in integrating content information with their social information giving rise to social networking sites. Social networking sites such as Facebook, Twitter, etc., completely depend on individual users for content generation. Each of these social networking sites are Single-Platform based. With an increase in social networking sites, Single-Platform has a limitation where significant user interests are always left behind. 1|P a g e
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