Interestingness is not a dichotomy: Introducing softness in constrained pattern mining

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Abstract

The paradigm of pattern discovery based on constraints was introduced with the aim of providing to the user a tool to drive the discovery process towards potentially interesting patterns, with the positive side effect of achieving a more efficient computation. So far the research on this paradigm has mainly focussed on the latter aspect: the development of efficient algorithms for the evaluation of constraint-based mining queries. Due to the lack of research on methodological issues, the constraint-based pattern mining framework still suffers from many problems which limit its practical relevance. As a solution, in this paper we introduce the new paradigm of pattern discovery based on Soft Constraints. Albeit simple, the proposed paradigm overcomes all the major methodological drawbacks of the classical constraint-based paradigm, representing an important step further towards practical pattern discovery. © Springer-Verlag Berlin Heidelberg 2005.

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Bistarelli, S., & Bonchi, F. (2005). Interestingness is not a dichotomy: Introducing softness in constrained pattern mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3721 LNAI, pp. 22–33). https://doi.org/10.1007/11564126_8

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