Intelligent Courses Recommendation System of Collaborative Filtering Algorithm Based on K-means Clustering under Spark Platform

DOI

10.2991/assehr.k.220504.368How to use a DOI?

Keywords

Spark; Elective; Collaborative filtering recommendation; K-means

Abstract

Students in Chinese universities face a variety of electives. Their choice of the course impacts their scope of knowledge and their grade point, which influences their career or further learning. But in most condition, the most appropriate option will not be chosen due to the lack of detail and reference.

Intelligent recommendation system was applied in multiple fields, collaborative filtering algorithm is one of common recommendation algorithm and is widely used. However, a collaborative filtering algorithm has the drawback in accuracy and user similarity. In that case, an improved algorithm based on K-means clustering is applied. The improved algorithm uses Dichotomous K-means algorithm to deal with the long distance of cluster centroid. As original similarity algorithm leads to the result of low user similarity, a mixed algorithm is applied.

Traditional methodology of data computing and data storing cannot handle the demand of that much data set. As a big data platform, Spark has become a popular solution to these problems. University management combined with big data is a tendency[4].

Copyright

© 2022 The Authors. Published by Atlantis Press SARL.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license.

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TY  - CONF
AU  - Zhaowei Chen
PY  - 2022
DA  - 2022/06/01
TI  - Intelligent Courses Recommendation System of Collaborative Filtering Algorithm Based on K-means Clustering under Spark Platform
BT  - Proceedings of the 2022 8th International Conference on Humanities and Social Science Research (ICHSSR 2022)
PB  - Atlantis Press
SP  - 2041
EP  - 2045
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.220504.368
DO  - 10.2991/assehr.k.220504.368
ID  - Chen2022
ER  -