Improvised Cloud Based Venue Recommendation Framework
[1]
Roshni Vikas Misar, Everest Institute of Technology, Aurangabad, Maharashtra, India.
[2]
Balkrishna Patil, Everest Institute of Technology, Aurangabad, Maharashtra, India.
[3]
Rajesh Autil, Everest Institute of Technology, Aurangabad, Maharashtra, India.
The Recommendation systems is the technological development in technology trend. Most of recommendation systems is totally based on past behavior which is termed as collaborative filtering based recommendation system which suffers some problems such as data sparseness, cold start etc. This paper is totally based bi-objective recommendation framework (BORF). Bi-objective framework is cloud based framework for mobile social network. This paper proposed a system for venue recommendation on the basis of rating given by user and nearest place to user on the basis of longitude and latitude. This paper optimized both scalar and vector optimization. Some algorithms are used for scalar and vector optimization as weighted sum approach and evolutionary NSGA-II respectively.
BORF, Collaborative Filtering (CF), Non-dominated Sorting Genetic Algorithm (NSGA-II)
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Internal journal of Advance scientific research and engineering trends || Volume 1 ||Issue 5 ||Sept 2016||ISSN (Online) 2456-0774 improvised cloud based venue recommendation content aware using KNN method.
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