Abstract
Identifying relationship between attribute variables from different data sources is an emerging field in data mining. However, currently there seldom exist effective methods designed for this particular problem. In this paper, a novel approach for inter-variable correlation prediction is proposed through the employment of the concept of connected-triple, and implemented with fuzzy logic. By the use of link strength measurements and fuzzy inference, the job of detecting similar or related variables can be accomplished via examining the link relation patterns. Comparative experimental investigations are carried out, demonstrating the potential of the proposed work in generating acceptable predicted results, while involving only simple computations.
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Li, Z., Shang, C., Shen, Q. (2018). Fuzzy Connected-Triple for Predicting Inter-variable Correlation. In: Chao, F., Schockaert, S., Zhang, Q. (eds) Advances in Computational Intelligence Systems. UKCI 2017. Advances in Intelligent Systems and Computing, vol 650. Springer, Cham. https://doi.org/10.1007/978-3-319-66939-7_5
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DOI: https://doi.org/10.1007/978-3-319-66939-7_5
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