— This paper introduces a quantitative method for social data analysis, which is based on the use of categorical data clustering. More specifically, we employ categorical data cl...
Meaningfully integrating massive multi-experimental genomic data sets is becoming critical for the understanding of gene function. We have recently proposed methodologies for integ...
The scalability problem in data mining involves the development of methods for handling large databases with limited computational resources. In this paper, we present a two-phase...
Although very widely used in unsupervised data mining, most clustering methods are affected by the instability of the resulting clusters w.r.t. the initialization of the algorithm ...
—In this paper, we have modified a constrained clustering algorithm to perform exploratory analysis on gene expression data using prior knowledge presented in the form of constr...
Erliang Zeng, Chengyong Yang, Tao Li, Giri Narasim...