Akihiko Nakase

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Matrix clustering is a new data mining method which extracts a dense sub-matrix from a large sparse binary matrix. We propose an e cient algorithm named the ping-pong algorithm which enables real-time mining of a large sparse matrix. This article describes the application of matrix clustering to Web usage mining. Matrix clustering can be applied to Web(More)
This paper describes external reference management and distributed unification in a distributed implementation of a concurrent logic programming language KL1. This implementation is based on the KLIC system. KLIC has a feature calledgeneric objects that enable easy modification and extension of the system without changes in the core implementation. This(More)
This paper proposes a parallel data-mining algorithm and its implementation on a PC cluster. The decision tree is a widely used data-mining algorithm for classifying records in a database. Simple parallelization of decision tree generation is not efficient because of the load imbalance caused by the form of the generated tree. The SPRINT algorithm solves(More)
Abst rac t . Quiescence detection is a fundamental facility for parallel and distributed processing. This paper describes schemes for quiescence detection in a distributed KLIC implementation. KLIC is a portable implementation of concurrent logic programming language KL1. Termination is detected using the weighted throw counting (WTC) scheme. Based on the(More)