A Hybrid Recommender System Using Bio Inspired Clustering Technique For Top N Item Recommendation

Document Type : Primary Research paper

Authors

1 Assistant Professor, Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India

2 Assistant Professor, Computer Technology, Kongu Engineering College Perundurai, Tamilnadu, India

Abstract

Now, we all are living in the information rich world, people depend on technologies
for their everyday activities. The technologies and its massive growth give rich set of
benefits and services to the users. The entire world is running towards digitization. The
people, company, organizations and institutions are making their everyday activities in digital
form. The growth of digitization gives better solution for information search.
But, on the other end, people struggle with information overloaded. We are finding difficult
to get the desired information from the internet. Sometimes it is a great challenge
to get the wished data from the internet. This is the reason behind the research in
recommendation and invention of recommender systems. A smart recommender
system provides better solution for information search and its related issues. Many
recommender systems and tools are widely used by the e-commerce applications, but the
accuracy of the tools still needs improvement. The previous research in the
area of recommendation comes under collaborative filtering, user content search
and by combining the best of the above mentioned. The proposed work focuses on the
combination of the first two methods which are mentioned earlier. This research attempts
to utilize the possible features of the two clustering techniques to achieve the user interest
prediction. The item ratings are the major parameters taken for evaluating the
efficiency of the proposed work. The data set are taken from Imdb database
(www.imdb.com) and MovieLens dataset to test the accuracy of the proposed system.

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