The ability to store vast quantities of data and the emergence of high speed networking have led to intense interest in distributed data mining. However, privacy concerns, as well ...
Mean shift clustering is a powerful unsupervised data
analysis technique which does not require prior knowledge
of the number of clusters, and does not constrain the shape
of th...
Process Mining refers to the extraction of process models from event logs. Real-life processes tend to be less structured and more flexible. Traditional process mining algorithms...
R. P. Jagadeesh Chandra Bose, Wil M. P. van der Aa...
Clustering is an essential data mining task with various types of applications. Traditional clustering algorithms are based on a vector space model representation. A relational dat...
This paper provides a novel Web image clustering methodology based on their associated texts. In our approach, the semantics of Web images are firstly represented into vectors of t...