The process of partitioning a large set of patterns into disjoint and homogeneous clusters is fundamental in knowledge acquisition. It is called Clustering in the literature and it is applied in various fields including data mining, statistical data analysis, compression and vector quantization. The k-means is a very popular algorithm and one of the best for implementing the clustering process. The k-means has a time complexity that is dominated by the product of the number of patterns, the number of clusters, and the number of iterations. Also, it often converges to a local minimum. In this paper, we present an improvement of the k-means clustering algorithm, aiming at a better time complexity and partitioning accuracy. Our approach reduces the number of patterns that need to be examined for similarity, in each iteration, using a windowing technique. The latter is based on well known spatial data structures, namely the range tree, that allows fast range searches. © 2002 Elsevier Science (USA)

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Purpose -This paper aims to present a methodology for activity-based costing, which combines simulation modeling and association rule mining, one of the core data-mining techniques. The objective of the proposed methodology is to deal with the problem of defining cost drivers. Design/methodology/approach -Activity-based costing uses the output produced by the simulation of cost drivers as inputs. As opposed to the integration of the ABC technique with simulation modeling, the possibility of estimating an empirical distribution of the simulated cost drivers does not exist in the proposed methodology. This is achieved with the use of data-mining techniques and is based on the proposition that, if an association is found between a cost driver, whose estimation or calculation is time-consuming, and another cost driver, which can easily be estimated or calculated, then the latter can lead to the estimation or calculation of the former. Findings -The extracted association rules correspond to existing dependencies between the cost drivers. Originality/value -The paper presents a combined methodology to deal with the problem of defining cost drivers in activity-based costing. An example of the proposed methodology in healthcare is also presented.