Correlation clustering is a technique for aggregating data based on qualitative information about which pairs of objects are labeled ‘similar’ or ‘dissimilar.’ Because the optimization problem is NP-hard, much of the previous literature focuses on finding approximation algorithms. In this paper we explore how to solve the correlation clustering objective exactly when the data to be clustered ca...

background: one of the factors that can improve self-concept and performance of staff is professional maturity. professional maturity can also solve the problems of self-concept. the purpose of this paper was to identify the relationship between the dimensions of self-concept and professional maturity.   materials and methods: this relative applicable study was performed on all the personnel (n...

In this paper, we develop a local rank correlation measure which quantifies the performance of dimension reduction methods. The local rank correlation is easily interpretable, and robust against the extreme skewness of nearest neighbor distributions in high dimensions. Some benchmark datasets are studied. We find that the local rank correlation closely corresponds to our visual interpretation o...