データマイニングと知識発見

―統計学の視点から―

抄録

Recent vast development of high-speed computer and large storing facilities together with network environment enables us to construct very large or sometimes huge databases such as giga-byte level. In order to extract novel, useful and also interpretable information from those databases, new technology becomes potentially important and being called for in various research and commercial fields. Data mining and knowledge discovery in databases(KDD)are the names given to such activity which involves database technology, machine learning, data visualization and statistics. Since we deal with data, statistics and statisticians are to be expected to play an essential role in data mining and KDD as well. Data mining, however, differs from traditional statistics on some dimensions, in which?gscale?his the most important one. The present paper first reviews recent achievement of data mining and KDD from a statistical viewpoint. Although some differences between data mining and traditional statistics are pointed out, it will be emphasized here that those two areas are closely related and should be recognized as complement to each other. Some important research areas are also discussed. One important message of this review is that statisticians should be involved in this new activity and should play a vital role in developing new methodologies and also in finding various application areas in practice.