Correlation Clustering was defined by Bansal, Blum, and Chawla as the problem of clustering a set of elements based on a possibly inconsistent binary similarity function between e...
We present an online adaptive clustering algorithm in a decision tree framework which has an adaptive tree and a code formation layer. The code formation layer stores the represen...
In this paper, we present an agglomerative fuzzy K-Means clustering algorithm for numerical data, an extension to the standard fuzzy K-Means algorithm by introducing a penalty term...
Mark Junjie Li, Michael K. Ng, Yiu-ming Cheung, Jo...
Clustering is often used to discover structure in data. Clustering systems differ in the objective function used to evaluate clustering quality and the control strategy used to se...
Abstract—Community detection or cluster detection in networks is a well-studied, albeit hard, problem. Given the scale and complexity of modern day social networks, detecting “...
Yang Yang, Yizhou Sun, Saurav Pandit, Nitesh V. Ch...