Many real datasets have uncertain categorical attribute values that are only approximately measured or imputed. Uncertainty in categorical data is commonplace in many applications...
The unsupervised nature of cluster analysis means that objects can be clustered in many different ways. This means that different clustering algorithms can lead to vastly different...
Traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. While domain knowledge is always the bes...
This paper presents a novel algorithm for document clustering based on a combinatorial framework of the Principal Direction Divisive Partitioning (PDDP) algorithm [1] and a simpli...
Recently, privacy issues have become important in clustering analysis, especially when data is horizontally partitioned over several parties. Associative queries are the core retr...