Publication:
On Concept Lattices as Information Channels

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ISSN: 1613-0073
ISBN: 978-80-8152-159-1
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2014-10
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Ceur Workshop Proceedings
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Abstract
This paper explores the idea that a concept lattice is an information channel between objects and attributes. For this purpose we study the behaviour of incidences in L-formal contexts where L is the range of an information-theoretic entropy function. Examples of such data abound in machine learning and data mining, e.g. confusion matrices of multi-class classifers or document-term matrices. We use a wellmotivated information-theoretic heuristic, the maximization of mutual information, that in our conclusions provides a favour of feature selection providing and information-theory explanation of an established practice in Data Mining, Natural Language Processing and Information Retrieval applications, viz. stop-wording and frequency thresholding. We also introduce a post-clustering class identi cation in the presence of confusions and a favour of term selection for a multi-label document classifcation task.
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Proceedings of: 11th International Conference on Concept Lattices and Their Applications (CLA 2014). Kosice, Slovakia, October 07-10, 2014.
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Concept Lattices, Information Channels
Bibliographic citation
Bertet, K. and Rudolph, S. (eds.) (2014). CLA 2014: Concept Lattices and Their Applications: Volume I: Eleventh International Conference on Concept Lattices and Their Applications. Kosice, Slovakia, October 07-10, 2014. Proceedings. (pp. 119-130). CEUR workshop Proceedings.