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2017 | OriginalPaper | Buchkapitel

3. Applications, Variants, and Extensions of Redescription Mining

verfasst von : Esther Galbrun, Pauli Miettinen

Erschienen in: Redescription Mining

Verlag: Springer International Publishing

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Abstract

Redescription mining is a data analysis task that aims at finding distinct common characterizations of the same objects. After defining the core problem and presenting algorithmic techniques to solve this task, we look in this chapter at some of the applications, variants, and extensions of redescription mining. We start by outlining different applications, as examples of how the method can be used in various domains. Next, we present two problem variants, namely, relational redescription mining and storytelling. The former aims at finding alternative descriptions for groups of objects in a relational data set, while the goal in the latter is to build a sequence of related queries in order to establish a connection between two given queries. Finally, we point out extensions of the task that constitute possible directions for future research. In particular, we discuss how redescription mining could be augmented with richer query languages and consider going beyond pairs of queries to multiple descriptions.

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Titel: Applications, Variants, and Extensions of Redescription Mining
verfasst von: Esther Galbrun
Pauli Miettinen
Verlag: Springer International Publishing
Buch: Redescription Mining
Print ISBN: 978-3-319-72888-9

Electronic ISBN: 978-3-319-72889-6

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-72889-6_3

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