Recommendation System Based on Prediction of User Behaviour with Hybrid Approach |
Author(s): |
| Sufiyan Dagli , PROF. RAM MEGHE INSTITUTE OF TECHNOLOGY AND RESEARCH; Ankit Mune, PROF. RAM MEGHE INSTITUTE OF TECHNOLOGY AND RESEARCH; Ketan Gadwale, PROF. RAM MEGHE INSTITUTE OF TECHNOLOGY AND RESEARCH; Dharti Akkawar, PROF. RAM MEGHE INSTITUTE OF TECHNOLOGY AND RESEARCH; Dhanashree Kaurase, PROF. RAM MEGHE INSTITUTE OF TECHNOLOGY AND RESEARCH |
Keywords: |
| Content Based, Collaborative Approach, K-Mean Algorithm, Hidden Markov Model, Clustering |
Abstract |
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Nowadays, the usage of e-commerce is growing day by day, so online users are also rising. Every user spends their most of the time on e-commerce websites and their behavior is different from one another. E-commerce has become very competitive so, knowing user’s behavior has become prior concern. Most of the e-commerce platforms are using either content based or collaborative approach to predict user behavior. Collaborative approach has become obsolete. Many e-commerce websites mainly rely on the content based approach. But for better recommendation, it is important to make use of the user data as well. We propose design and implementation of hybrid system by K-mean algorithm and Hidden Markov Model. Machine learning regression algorithms are used to fetch user’s priorities and clustering of data through K-mean algorithm. |
Other Details |
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Paper ID: IJSRDV6I90129 Published in: Volume : 6, Issue : 9 Publication Date: 01/12/2018 Page(s): 111-113 |
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