Alleviating the Cold Start Problem in Recommender Systems Based on Modularity Maximization Community Detection Algorithm

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ISSN Print: 2153-1285
ISSN Online: 2153-1293
www.scirp.org/journal/cs
E-mail: cs@scirp.org

"Alleviating the Cold Start Problem in Recommender Systems Based on Modularity Maximization Community Detection Algorithm"
written by S. Vairachilai, M. K. Kavithadevi, M. Raja,
published by Circuits and Systems, Vol.7 No.8, 2016

has been cited by the following article(s):

[1]	Recommender Systems: An Overview, Research Trends, and Future Directions
	2021

[2]	Researching on the Cold Start Technology of New Broadcast Television Storage Resource Allocation
	2021

[3]	Collaborative Filtering Recommendation Algorithm for Heterogeneous Data Mining in the Internet of Things
	2019

[1]	Assessment of Discrete BAT-Modified (DBAT-M) Optimization Algorithm for Community Detection in Complex Network Arabian Journal for Science and Engineering, 2022 DOI:10.1007/s13369-022-07229-y

[2]	Researching on the Cold Start Technology of New Broadcast Television Storage Resource Allocation 2021 IEEE 6th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA), 2021 DOI:10.1109/ICCCBDA51879.2021.9442551

[3]	Collaborative Filtering Recommendation Algorithm for Heterogeneous Data Mining in the Internet of Things IEEE Access, 2019 DOI:10.1109/ACCESS.2019.2935224

[4]	Collaborative Filtering Recommender System: Comparative Survey on Cold-Start Issue Indian Journal of Science and Technology, 2018 DOI:10.17485/ijst/2018/v11i20/116392

[5]	Collaborative Filtering Recommender System: Comparative Survey on Cold-Start Issue Indian Journal of Science and Technology, 2018 DOI:10.17485/ijst/2018/v11i22/116392

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