Solving distribution problems in content-based recommendation system with gaussian mixture model
- 25 May 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in Applied Intelligence
- Vol. 52 (2), 1602-1614
- https://doi.org/10.1007/s10489-021-02429-9
Abstract
No abstract availableKeywords
This publication has 21 references indexed in Scilit:
- A Knowledge-Based Recommendation System That Includes Sentiment Analysis and Deep LearningIEEE Transactions on Industrial Informatics, 2019
- Reliability quality measures for recommender systemsInformation Sciences, 2018
- An expert recommendation algorithm based on Pearson correlation coefficient and FP-growthCluster Computing, 2018
- Latent semantic indexing and convolutional neural network for multi-label and multi-class text classificationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2017
- A review on recommender systemsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2017
- Joint Learning of the Embedding of Words and Entities for Named Entity DisambiguationPublished by Association for Computational Linguistics (ACL) ,2016
- Music Recommendation System Design Based on Gaussian Mixture ModelPublished by Atlantis Press SARL ,2015
- Euclidean Distance Geometry and ApplicationsSIAM Review, 2014
- Content-based Recommender Systems: State of the Art and TrendsPublished by Springer Science and Business Media LLC ,2010
- Dirichlet Process Gaussian Mixture Models: Choice of the Base DistributionJournal of Computer Science and Technology, 2010