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Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing pp 161–177Cite as

A Discovery Method of Anteroposterior Correlation for Big Data Era

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 569))

Abstract

In this paper, we present a new knowledge extraction method on Big data era.We introduce new concepts, anteroposterior correlation, and propose an extraction method of anteroposterior correlation. The anteroposterior correlation means the correlation based on the time anteroposterior relation. We consider that Heterogeneity, continuity, and visualization are the most critical features of Big data analytics, which provides a scale and connection merits based on them. No current data analysis methods are based on opened assumptions. Big data analytics provides a new data analysis method based on opening assumptions. In this paper, we especially focus on an aspect of heterogeneity. We discover a correlation in consideration of the continuity of time. By our method, we effectively discover relationships between heterogeneous things, events and phenomena. The anteroposterior correlations are represented in relative comparison with each conditional probability distribution. The one of the features of our method is a measurement correlation by using conditional probability. That is, we calculate the correlation relative by representing all in conditional probability, no absolutely. Our method is determined higher correlation by comparison to each heterogeneous thing, event and phenomenon. This is the most important points on the Big data era. When you apply current association rule extraction techniques, you obtain too big rule base to organize them. By our method, we realize the one of the methods for decision mining.

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Authors and Affiliations

  1. The Center for Global Communications (GLOCOM), International University of Japan, Tokyo, Japan

    Takafumi Nakanishi

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  1. Takafumi Nakanishi
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Correspondence to Takafumi Nakanishi .

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  1. Software Engineering & Information Technology Institute, Central Michigan University, Mt. Pleasant, Michigan, USA

    Roger Lee

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Nakanishi, T. (2015). A Discovery Method of Anteroposterior Correlation for Big Data Era. In: Lee, R. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. Studies in Computational Intelligence, vol 569. Springer, Cham. https://doi.org/10.1007/978-3-319-10389-1_12

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  • DOI: https://doi.org/10.1007/978-3-319-10389-1_12

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10388-4

  • Online ISBN: 978-3-319-10389-1

  • eBook Packages: EngineeringEngineering (R0)

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