<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The article presents current approaches to solving the problem of building recommender systems designed to intellectualize the user interface of online stores. Much attention is paid to modern methods of building recommender systems, analysing their strengths and weaknesses. Of greatest interest are the criteria for selecting effective methods for specific online stores and the authors’ concept of a typical recommender system of electronic commerce.</p></abstract>

The article presents current approaches to solving the problem of building recommender systems designed to intellectualize the user interface of online stores. Much attention is paid to modern methods of building recommender systems, analysing their strengths and weaknesses. Of greatest interest are the criteria for selecting effective methods for specific online stores and the authors’ concept of a typical recommender system of electronic commerce.

Modern Approaches to Building Recommender Systems for Online Stores

Financial University under the Government of the Russian Federation

Applied Computer Systems

This work is licensed under the Creative Commons Attribution 4.0 Public License.

{"article-title":"Modern Approaches to Building Recommender Systems for Online Stores"}

The article presents current approaches to solving the problem of building recommender systems designed to intellectualize the user interface of online stores....

Modern Approaches to Building Recommender Systems for Online Stores

Online veröffentlicht: 20. Juni 2019

Seitenbereich: 18 - 24

DOI: https://doi.org/10.2478/acss-2019-0003

Schlüsselwörter
Collaborative filtering, combined co-filtering, content filtering, typical recommender system

© 2019 Lyudmila Onokoy et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 Public License.

Modern Approaches to Building Recommender Systems for Online Stores

Online veröffentlicht: 20. Juni 2019

Seitenbereich: 18 - 24

DOI: https://doi.org/10.2478/acss-2019-0003

SchlüsselwörterCollaborative filtering, combined co-filtering, content filtering, typical recommender system

© 2019 Lyudmila Onokoy et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 Public License.

Schlüsselwörter
Collaborative filtering, combined co-filtering, content filtering, typical recommender system