Improved movie recommendations based on a hybrid feature combination method

Article


Alshammari, G., Kapetanakis, S., Alshammari, A., Polatidis, N. and Petridis, M. 2019. Improved movie recommendations based on a hybrid feature combination method. Vietnam Journal of Computer Science. 6 (3), pp. 363-376. https://doi.org/10.1142/s2196888819500192
TypeArticle
TitleImproved movie recommendations based on a hybrid feature combination method
AuthorsAlshammari, G., Kapetanakis, S., Alshammari, A., Polatidis, N. and Petridis, M.
Abstract

Recommender systems help users find relevant items efficiently based on their interests and historical interactions with other users. They are beneficial to businesses by promoting the sale of products and to user by reducing the search burden. Recommender systems can be developed by employing different approaches, including collaborative filtering (CF), demographic filtering (DF), content-based filtering (CBF) and knowledge-based filtering (KBF). However, large amounts of data can produce recommendations that are limited in accuracy because of diversity and sparsity issues. In this paper, we propose a novel hybrid method that combines user–user CF with the attributes of DF to indicate the nearest users, and compare four classifiers against each other. This method has been developed through an investigation of ways to reduce the errors in rating predictions based on users’ past interactions, which leads to improved prediction accuracy in all four classification algorithms. We applied a feature combination method that improves the prediction accuracy and to test our approach, we ran an offline evaluation using the 1M MovieLens dataset, well-known evaluation metrics and comparisons between methods with the results validating our proposed method.

PublisherWorld Scientific Publishing Co. Pte Ltd
JournalVietnam Journal of Computer Science
ISSN2196-8888
Electronic2196-8896
Publication dates
Online08 Jul 2019
Print14 Aug 2019
Publication process dates
Deposited23 Jul 2019
Accepted13 Jun 2019
Output statusPublished
Publisher's version
License
Copyright Statement

© The Author(s). This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License. Further distribution of this work is permitted, provided the original work is properly cited.

Digital Object Identifier (DOI)https://doi.org/10.1142/s2196888819500192
LanguageEnglish
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