On a correlational clustering of integers
arXiv:1404.0904v11.26 citations
Originality Synthesis-oriented
AI Analysis
This work addresses a domain-specific clustering problem for integer data, but appears incremental as it applies an existing concept to a new context.
The paper tackles the problem of correlation clustering for integers using the greatest common divisor, aiming to find partitions with minimal conflicts.
Correlation clustering is a concept of machine learning. The ultimate goal of such a clustering is to find a partition with minimal conflicts. In this paper we investigate a correlation clustering of integers, based upon the greatest common divisor.