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Recommender Systems Survey : A Multi-Criteria Based Approach


Sheetal R Thakare , University Of Mumbai India


recommender system, criterion, multi-criteria based, content-based filtering, collaborative filtering, demographic data, personalization, prediction


With the advent of Internet & E-Commerce applications people are exposed to mines of information and variety of products to choose from. In such situation it is quite obvious to get lost in, exploring abundance of products and related information while zeroing down the product to buy from the available many. This causes the waste of large amount of precious time and may at the same time, create confusion in the minds of prospective on-line shoppers regarding purchasing decision to be made, leading to in-vein search and unfruitful buying attempt. As a consequence, the role of user modeling and personalized information access is becoming crucial, users need a personalized support in sifting through large amounts of available information, according to their interests and tastes. Recommender systems play an important role in such scenario by presenting the buyer with the ranked list of products preferred by existing buyers for the same/similar products. The number of features of the product used to determine the order of the product in the ranked list will define the approach used by Recommender system.

Other Details

Paper ID: IJSRDV3I1485
Published in: Volume : 3, Issue : 1
Publication Date: 01/04/2015
Page(s): 924-929

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