The emergence of the Semantic Web has led to the creation of large semantic knowledge bases, often in the form of RDF databases. Improving the performance of RDF databases necessit...
The target of machine learning is a predictive model that performs well on unseen data. Often, such a model has multiple intended uses, related to different points in the tradeoff ...
Alan P. Reynolds, David W. Corne, Michael J. Chant...
Real-world, multiple-typed objects are often interconnected, forming heterogeneous information networks. A major challenge for link-based clustering in such networks is its potent...
This paper explores the generation of candidates, which is an important step in frequent itemset mining algorithms, from a theoretical point of view. Important notions in our prob...
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...