Book review: Three perspectives of data mining

Authors:
Zhi-Hua Zhou
Affiliations:
National Laboratory for Novel Software Technology, Nanjing University, Hankou Road 22, Nanjing 210093, People's Republic of China
Venue:
Artificial Intelligence
Year:
2003

Citing 6
Cited 8

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Abstract

This paper reviews three recent books on data mining written from three different perspectives, i.e., databases, machine learning, and statistics. Although the exploration in this paper is suggestive instead of conclusive, it reveals that besides some common properties, different perspectives lay strong emphases on different aspects of data mining. The emphasis of the database perspective is on efficiency because this perspective strongly concerns the whole discovery process and huge data volume. The emphasis of the machine learning perspective is on effectiveness because this perspective is heavily attracted by substantive heuristics working well in data analysis although they may not always be useful. As for the statistics perspective, its emphasis is on validity because this perspective cares much for mathematical soundness behind mining methods.