Product Recommendation Techniques for Ecommerce - past, present and future
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2012, Vol 1, Issue 9
Abstract
With the advent of emerging technologies and the rapid growth of Internet, the world is moving towards e-world where most of the things are digitized and available on a mouse click. Most of the commercial transactions are performed on Internet with the help of on-line shopping. The huge amount of data puts an extra overload to the user in performing on-line task. Product recommendation techniques are being used widely to reduce this extra overload and recommend the scrutinized product to the customers. Collaborative filtering, Association rules and web mining are on top amongst the techniques that is being used for recommendation technology. In this paper we try to give an overview of these recommendation techniques with suitable examples and illustrative diagrams, and change of trends in it with respect to time. Various diagrammatic representations are illustrated. Also a future direction of research in this area is indicated. And finally we conclude that there is a need of an extra effort to overcome limitations in existing techniques.
Authors and Affiliations
Shahab Saquib Sohail , Dr. Rashid Ali
Keywords
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