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Finding Segmentations of Sequences

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Abstract

We describe a collection of approaches to inductive querying systems for data that contain segmental structure. The main focus in this chapter is on work done in Helsinki area in 2004-2008. Segmentation is a general data mining technique for summarizing and analyzing sequential data. We first introduce the basic problem setting and notation.We then briefly present an optimal way to accomplish the segmentation, in the case of no added constraints. The challenge, however, lies in adding constraints that relate the segments to each other and make the end result more interpretable for the human eye, and/or make the computational task simpler. We describe various approaches to segmentation, ranging from efficient algorithms to added constraints and modifications to the problem. We also discuss topics beyond the basic task of segmentation, such as whether an output of a segmentation algorithm is meaningful or not, and touch upon some applications.

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Authors and Affiliations

  1. Helsinki Institute for Information Technology, University of Helsinki and Aalto University School of Science and Technology, Helsink, Finland

    Ella Bingham

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  1. Ella Bingham
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Correspondence to Ella Bingham .

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Editors and Affiliations

  1. , Department of Knowledge Technologies, Jozef Stefan Institute, Jamova 39, Ljubljana, 1000, Slovenia

    Sašo Džeroski

  2. , Mathematics and Computer Science, University of Antwerp, Middelheimlaan 1, Antwerpen, B-2020, Belgium

    Bart Goethals

  3. , Dept. of Knowledge Technologies, Jožef Stefan Institute, Jamova cesta 39, Ljubljana, SI-1000, Slovenia

    Panče Panov

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Bingham, E. (2010). Finding Segmentations of Sequences. In: Džeroski, S., Goethals, B., Panov, P. (eds) Inductive Databases and Constraint-Based Data Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7738-0_8

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  • DOI: https://doi.org/10.1007/978-1-4419-7738-0_8

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-7737-3

  • Online ISBN: 978-1-4419-7738-0

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