Collaborative Filtering Approach of Keyword Aware Service Recommendation for Big Data Applications on Map-Reduce
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 7
Abstract
Recommender systems are shown as valuable tools for providing acceptable recommendations to users. Within the last decade, the number of customers shopping online, services and on-line data has grown quickly, yielding the Big Data analysis as a drawback for service recommender systems. Recommendations systems have been very popular in research community, where many approach to provide recommendations to users are suggested. Most of existing service recommender systems present an equivalent ratings and rankings of services to completely different users while not considering various users' preferences, and thus fails to fulfill users' personalized needs. Proposed Service recommendation generates a personalized service recommendation list taking into consideration of the preferences of the user and recommends appropriate service to the user effectively. Keywords are used to indicate users’ preferences. Filtering rule is adopted to come up with more accurate recommendations. The proposed method is implemented on Hadoop, a widely used platform for distributed processing of Big Data across clusters of servers using the Map Reduce data processing paradigm. Thus it is scalable and efficient in Big Data environment.
Authors and Affiliations
Pavan Shanbhag, Asst Prof Leena Sakri
Keywords
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