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Transactions on Rough Sets VI pp 308–328Cite as

Discovering Association Rules in Incomplete Transactional Databases

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Part of the book series: Lecture Notes in Computer Science ((TRS,volume 4374))

Abstract

The problem of incomplete data in the data mining is well known. In the literature many solutions to deal with missing values in various knowledge discovery tasks were presented and discussed. In the area of association rules the problem was presented mainly in the context of relational data. However, the methods proposed for incomplete relational database can not be easily adapted to incomplete transactional data. In this paper we introduce postulates of a statistically justified approach to discovering rules from incomplete transactional data and present the new approach to this problem, satisfying the postulates.

Research has been supported by the grant No 3 T11C 002 29 received from Polish Ministry of Education and Science.

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Authors and Affiliations

  1. Institute of Computer Science, Warsaw University of Technology,  

    Grzegorz Protaziuk & Henryk Rybinski

Authors
  1. Grzegorz Protaziuk
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  2. Henryk Rybinski
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Editor information

James F. Peters Andrzej Skowron Ivo Düntsch Jerzy Grzymała-Busse Ewa Orłowska Lech Polkowski

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Protaziuk, G., Rybinski, H. (2007). Discovering Association Rules in Incomplete Transactional Databases. In: Peters, J.F., Skowron, A., Düntsch, I., Grzymała-Busse, J., Orłowska, E., Polkowski, L. (eds) Transactions on Rough Sets VI. Lecture Notes in Computer Science, vol 4374. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71200-8_17

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  • DOI: https://doi.org/10.1007/978-3-540-71200-8_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71198-8

  • Online ISBN: 978-3-540-71200-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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