Advanced Information and Knowledge Processing

2016

DOI: 10.1007/978-3-319-28531-3_12

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Data Analysis and Data Mining

Sergei V. Chekanov

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Cited by 3 publications

References 10 publications

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A Flexible Mobility System Based on CHIP Architectures: The NETCHIP Research Project

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et al. 2018

2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Syst

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A Flexible Mobility System Based on CHIP Architectures: The NETCHIP Research Project

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et al. 2018

2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Syst

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Fuzzy Ontology based Approach for Flexible Association Rules Mining

2017

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Abstract-Data mining is used for extracting related data. The association rules approach is one of the used methods for analyzing, discovering and extracting knowledge and mining the relationships among raw data. Commonly, it is important to understand and discover such knowledge directly from huge records of items stored in a relational database. This paper proposes an approach for generating human-like fuzzy association rules based on fuzzy ontology. It focuses on enhancing the process of extracting association rules from a huge database respecting a predefined domain fuzzy ontology. Commonly, association rules mining based on crisp ontology is found to be more flexible than classical ones as it considers the relationships between concepts or items. Yet, crisp ontology suffers from the problem of information losing resulted from the rigid boundaries of crisp relationships, which are approximated to be 0 or 1, between concepts. In contrast, the smooth boundaries of fuzzy sets make it able to represent partial relationships that range from 0 to 1 between concepts in an ontology in a more flexible human-like manner. Consequently, generating fuzzy association rules based on fuzzy ontology makes it more human-like and reliable compared with other previous ones. An illustrative case study, on two different data sets, shows the added value of the proposed approach compared with some other recent approaches.

Performance Drivers in Global Production Networks: Analysis of Cause and Effect Relations between Influencing Factors and Performance of Production Sites

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et al. 2017

2017 Portland International Conference on Management of Engineering and Technology (PICMET)

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