Rank aggregation is an important task in many areas, nevertheless, none of rank aggregation algorithms is best for all cases. The main goal of this work is to develop a method, whi...
Alexey Zabashta, Ivan Smetannikov, Andrey Filchenk...
The importance of Markov blanket discovery algorithms is twofold: as the main building block in constraint-based structure learning of Bayesian network algorithms and as a techniqu...
Abstract. We present an exploratory data mining tool useful for finding patterns in the geographic distribution of independent UK-based music artists. Our system is interactive, h...
Topic modeling techniques have been widely used to uncover dominant themes hidden inside an unstructured document collection. Though these techniques first originated in the proba...
Abstract. Music recommender systems are lately seeing a sharp increase in popularity due to many novel commercial music streaming services. Most systems, however, do not decently t...
Efficient integration of renewable energy sources into the electricity grid has become one of the challenging problems in recent years. This issue is more critical especially for u...
Scientific impact plays a central role in the evaluation of the output of scholars, departments, and institutions. A widely used measure of scientific impact is citations, with ...
Many applications that use empirically estimated functions face a curse of dimensionality, because integrals over most function classes must be approximated by sampling. This paper...
Identifying the best machine learning algorithm for a given problem continues to be an active area of research. In this paper we present a new method which exploits both meta-level...
Salisu Abdulrahman, Pavel Brazdil, Jan N. van Rijn...