Recommender Systems

Author:

Polatidis Nikolaos1,Georgiadis Christos K.1

Affiliation:

1. Department of Applied Informatics, University of Macedonia, Thessaloniki, Greece

Abstract

Due to the rapid growth of the internet in conjunction with the information overload problem the use of recommender systems has started to become necessary for both e-businesses and customers. However there are other factors such as privacy and trust that make customers suspicious. This paper gives an overview of recommendation systems, the benefits that both the business and the customers have and an explanation of the challenges, which if faced can make the personalization process better for both parties. Moreover an outline of current studies is given along with an overview of Amazon's recommendations in order to clarify that the use of recommender systems is beneficial for an e-business in many ways and also for a valuable customer of such business.

Publisher

IGI Global

Subject

Law,Management of Technology and Innovation,Business and International Management,Management Information Systems

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. The bias beneath: analyzing drift in YouTube’s algorithmic recommendations;Social Network Analysis and Mining;2024-08-24

2. Applying Nonnegative Matrix Factorization for Underground Mining Method Selection Based on Mining Projects' Historical Data;International Journal of the Society of Materials Engineering for Resources;2024-03-31

3. Toward a Knowledge-based Personalised Recommender System for Mobile App Development;JUCS - Journal of Universal Computer Science;2021-02-28

4. An Improved Product Recommendation Method for Collaborative Filtering;IEEE Access;2020

5. Advanced Customer Activity Prediction Based on Deep Hierarchic Encoder-Decoders;2019 22nd International Conference on Control Systems and Computer Science (CSCS);2019-05

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