The problem of identifying approximately duplicate records in databases is an essential step for data cleaning and data integration processes. Most existing approaches have relied...
The paper presents an evaluation of four clustering algorithms: k-means, average linkage, complete linkage, and Ward’s method, with the latter three being different hierarchical...
The diameter k-clustering problem is the problem of partitioning a finite subset of Rd into k subsets called clusters such that the maximum diameter of the clusters is minimized. ...
AND/OR search spaces have recently been introduced as a unifying paradigm for advanced algorithmic schemes for graphical models. The main virtue of this representation is its sens...
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...