Manuscript Number : CSEIT1724210
Collaborative Filtering Based Product Recommendation System for Online Social Networks
Authors(3) :-Sanjeev Dhawan, Kulvinder Singh, Naveen Kumar
In recent years the demand of social networking websites has been increased due to frequent uses of these sites by people. Social Networks play important role in the product's recommendation because nowadays peoples are connected with each other through Facebook, Twitter, Google+ etc., so it is easy to recommend a product to friends by social websites that whether to go for this product or not. Even companies are marketing their products on these social media's. In this paper, an attempt has been made to discuss product recommendation system and its related techniques. This paper is divided into four sections. In section I, product recommendation system is discussed. In section II, works related to different papers has been discussed. Section III includes different existing techniques with their benefits and drawbacks. Section IV presents problem statement and in section V different performance metrics has been presented.
Faculty of Computer Science and Engineering , Department of Computer Science and Engineering, University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra-136119, Haryana, India.
Faculty of Computer Science and Engineering , Department of Computer Science and Engineering, University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra-136119, Haryana, India
M.Tech. Computer Engineering, University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra-136119, Haryana, India.
Social Networks (SNs), Products, Recommendation and Collaborative Filtering (CF).
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Published in : Volume 2 | Issue 5 | September-October 2017
Date of Publication : 2017-10-31
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 126-131
Manuscript Number : CSEIT1724210
Publisher : Technoscience Academy
URL : http://ijsrcseit.com/CSEIT1724210