Clustering is a data mining problem which finds dense regions in a sparse multi-dimensional data set. The attribute values and ranges of these regions characterize the clusters. ...
Recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the Web, deman...
Wide-area sensor infrastructures, remote sensors, RFIDs, and wireless sensor networks yield massive volumes of disparate, dynamic, and geographically distributed data. As such sen...
Ranga Raju Vatsavai, Olufemi A. Omitaomu, Joao Gam...
Skewed distributions appear very often in practice. Unfortunately, the traditional Zipf distribution often fails to model them well. In this paper, we propose a new probability di...
Frequent Pattern Mining (FPM) is a very powerful paradigm for mining informative and useful patterns in massive, complex datasets. In this paper we propose the Data Mining Templat...
Mohammed Javeed Zaki, Nilanjana De, Feng Gao, Paol...