Ants Torim
ABSTRACT
Binary data arise naturally in many fields including shopping carts, pass-fail tests, social networks etc. Descriptive data mining aims to discover a concise set of general patterns in these possibly noisy data. An important tool for describing binary data is Formal Concept Analysis (FCA) which describes the data through formal concepts. As the full lattice of formal concepts can become large even when dealing with relatively modest amounts of data there are several methods to reduce the number of concepts used to describe the data: selecting a subset of "interesting" concepts, finding a subset of concepts that cover the data fully etc. In this paper we apply a novel method of concept chain coverage generation to service use data of a telecommunications company. Concept chain coverage aims to cover the data not with single concepts but with chains of related concepts. The aim is not the full coverage but high enough coverage through a concise set of concept chains. We show that a relatively modest set of concept chains (4 to 10) can describe most of the data and that the performance of the algorithm is very acceptable for this case study.
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Index Terms
- Concise Description of Telecom Service Use Through Concept Chains
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