Latent Factor Model for Book Recommendation System ---Taking Douban as an Example

DOI

10.2991/icesed-19.2020.5How to use a DOI?

Keywords

recommendation system, Collaborative Filtering, latent factor model, gradient descent, classification

Abstract

Recommendation system is a type of web intelligence technology that can perform daily information filtering for users. It has a more and more important position in the Internet era, so the filtering technology has become a focus of it. This paper introduces a technique called latent factor model which belongs to Collaborative Filtering, and it can identify hidden themes or categories, and establish the relationship between features through implicit themes or categories. The article takes book recommendation system in Douban as an example to explain the kind of technology can contribute to improve the recommendation system.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hanqiao Yu
PY  - 2020/01
DA  - 2020/01
TI  - Latent Factor Model for Book Recommendation System ---Taking Douban as an Example
BT  - Proceedings of the 2019 International Conference on Education Science and Economic Development (ICESED 2019)
PB  - Atlantis Press
SP  - 221
EP  - 226
SN  - 2352-5428
UR  - https://doi.org/10.2991/icesed-19.2020.5
DO  - 10.2991/icesed-19.2020.5
ID  - Yu2020/01
ER  -