International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| papers | Analysis of Customer Churn for Quality-of-Service Parameters using Machine Learning Archana Paike, Sayali Ambavane Department of Computer Engineering, Government Polytechnic, Pune, Maharashtra, India Department of Computer Engineering, Government Polytechnic, Pune, Maharashtra, India DOI: 10.15680/IJIRCCE.2021.0907237 |
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| pdf/WbybZEIa7Kpb4DFD16X0Soj5OIdaghBVvMothiOC.pdf |
