Knowledge Discovery and Interestingness Measures: A Survey

Robert J. Hilderman

2012 · 60 citations · 51 references

Concepts

Abstract

Knowledge discovery in databases, also known as data mining, is the ecient discovery of previously unknown, valid, novel, potentially useful, and understandable patterns in large databases. It encompasses many dierent techniques and algorithms which dier in the kinds of data that can be analyzed and the form of knowledge representation used to convey the discovered knowledge. An important problem in the area of data mining is the development of eective measures of interestingness for ranking the discovered knowledge. In this report, we provide a general overview of the more successful and widely known data mining techniques and algorithms, and survey seventeen interestingness measures from the literature that have been successfully employed in data mining applications. 1 1

References

51