Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/48791
Title: Hybrid Cohort Rating Prediction Technique to leverage Recommender System
Authors: Dhanalakshmi, R
Sinha, B B
Keywords: Recommender System;Pearson Correlation;Adjusted Cosine similarity;Collaborative filtering;MAE;RMSE
Issue Date: Jul-2019
Publisher: NISCAIR-CSIR, India
Abstract: The long tail of diverse consumption of resources online by the customers raises a challenge for the e-commerce websites and service providers. Recommender system offers a vigorous way to cope up with the aforementioned challenge. In this paper, we have proposed a hybrid cohort rating prediction technique which relies on high cohort users and high cohort items to make predictions. Our model significantly improves the retention of recommender system showing encouraging results when compared with existing traditional recommender systems.
Page(s): 411-414
URI: http://nopr.niscair.res.in/handle/123456789/48791
ISSN: 0975-1084 (Online); 0022-4456 (Print)
Appears in Collections:JSIR Vol.78(07) [July 2019]

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