We present a general approximation technique for a large class of graph problems. Our technique mostly applies to problems of covering, at minimum cost, the vertices of a graph wit...
Bayesian networks (BNs) are used to represent and ef ciently compute with multi-variate probability distributions in a wide range of disciplines. One of the main approaches to per...
The notion of a map is a fundamental metaphor in spatial disciplines. However, there currently exist no adequate data models for maps that define a precise spatial data type for m...
Abstract—Skip Tree Graph is a novel, distributed, data structure for peer-to-peer systems that supports exact-match and order-based queries such as range queries efficiently. It...
Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classifier. M...