Abstract—Despite the considerable amount of research work on the application of Gabor filters in pattern classification, their design and selection have been mostly done on a t...
Abstract. We present a new distributed association rule mining (D-ARM) algorithm that demonstrates superlinear speed-up with the number of computing nodes. The algorithm is the fi...
In this paper we present the Relational Bayesian Classifier (RBC), a modification of the Simple Bayesian Classifier (SBC) for relational data. There exist several Bayesian classif...
This paper describes the need for mining complex relationships in spatial data. Complex relationships are defined as those involving two or more of: multi-feature co-location, sel...
We present a framework for clustering distributed data in unsupervised and semi-supervised scenarios, taking into account privacy requirements and communication costs. Rather than...
There is a ever-growing need to add structure in the form of semantic markup to the huge amounts of unstructured text data now available. We present the technique of shallow seman...
Sameer Pradhan, Kadri Hacioglu, Wayne Ward, James ...
A major obstacle to fully integrated deployment of many data mining algorithms is the assumption that data sits in a single table, even though most real-world databases have compl...
Alexandrin Popescul, Lyle H. Ungar, Steve Lawrence...
Collaborative Filtering (CF) techniques are becoming increasingly popular with the evolution of the Internet. E-commerce sites use CF systems to suggest products to customers base...
We present a mixture model based approach for learning individualized behavior models for the Web users. We investigate the use of maximum entropy and Markov mixture models for ge...
The Support Vector Machine (SVM) solution corresponds to the centre of the largest sphere inscribed in version space. Alternative approaches like Bayesian Point Machines (BPM) and...