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ECSQARU
2001
Springer
14 years 2 months ago
An Empirical Investigation of the K2 Metric
Abstract. The K2 metric is a well-known evaluation measure (or scoring function) for learning Bayesian networks from data [7]. It is derived by assuming uniform prior distributions...
Christian Borgelt, Rudolf Kruse
ECAI
2000
Springer
14 years 2 months ago
Designing Clustering Methods for Ontology Building - The Mo'K Workbench
This paper describes Mo’K, a configurable workbench that supports the development of conceptual clustering methods for ontology building. Mo’K is intended to assist ontology de...
Gilles Bisson, Claire Nedellec, Dolores Cañ...
STOC
1998
ACM
139views Algorithms» more  STOC 1998»
14 years 2 months ago
Approximation Schemes for Euclidean k-Medians and Related Problems
In the k-median problem we are given a set S of n points in a metric space and a positive integer k. We desire to locate k medians in space, such that the sum of the distances fro...
Sanjeev Arora, Prabhakar Raghavan, Satish Rao
ICCI
1991
14 years 1 months ago
On the k-Coloring of Intervals
The problem of coloring a set of n intervals (from the real line) with a set of k colors is studied. In such a coloring, two intersecting intervals must receive distinct colors. O...
Martin C. Carlisle, Errol L. Lloyd
AAAI
2006
13 years 11 months ago
kFOIL: Learning Simple Relational Kernels
A novel and simple combination of inductive logic programming with kernel methods is presented. The kFOIL algorithm integrates the well-known inductive logic programming system FO...
Niels Landwehr, Andrea Passerini, Luc De Raedt, Pa...