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ABSTRACT
Title |
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Rule Mining for Many-Valued Implications Using Concept Lattice |
Authors |
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Bhavana Jamalpur, Prof.SSVN Sarma, Nagendar Yamsani |
Keywords |
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Concept Analysis; many-valued concept; concept lattice; implications; data mining |
Issue Date |
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Nov 2017 |
Abstract |
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Every object contains properties/attributes which generally have binary values either on or off.
The basic issue is how to manage with multi-valued attributes which consists of different values for a single attribute. Conceptual scaling is used to discretize the attributes such as age, color, shape which contain many values. A concept lattice may contain multi-valued contexts which is an important issue in the theory of concept lattices. This paper discusses on scaling and construction of concept lattice for multi-valued context. Conversion of multi-valued into one-valued is the primary goal of this paper. By analyzing formal contexts, which are obtained after transformation. Construction of lattice and generation of implications with specific support and confidence for the contexts is shown experimentally |
Page(s) |
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686-694 |
ISSN |
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0975–3397 |
Source |
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Vol. 9, Issue.11 |
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