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2020 | OriginalPaper | Chapter

Optimal Rating Prediction in Recommender Systems

Authors : Bilal Ahmed, Li Wang, Waqar Hussain, M. Abdul Qadoos, Zheng Tingyi, Muhammad Amjad, Syed Badar-ud-Duja, Akbar Hussain, Muhammad Raheel

Published in: Data Science

Publisher: Springer Singapore

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Abstract

Recommendation systems are best choice to cope with the problem of information overload. These systems are commonly used in recent years help to match users with different items. The increasing amount of available data on internet in recent year’s pretenses some great challenges in the field of recommender systems. Main challenge is to predict the user preference and provide favorable recommendations. In this article, we present a new mechanism to improve the prediction accuracy in recommendations. Our method includes a discretization step and chi-square algorithm for attribute selection. Results on MovieLens dataset show that our technique performs well and minimize the error ratio.

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Metadata
Title
Optimal Rating Prediction in Recommender Systems
Authors
Bilal Ahmed
Li Wang
Waqar Hussain
M. Abdul Qadoos
Zheng Tingyi
Muhammad Amjad
Syed Badar-ud-Duja
Akbar Hussain
Muhammad Raheel
Copyright Year
2020
Publisher
Springer Singapore
Book
Data Science

Print ISBN: 978-981-15-2809-5

Electronic ISBN: 978-981-15-2810-1

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-15-2810-1_32

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