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Analysis of spatiotemporal data relationship using information granules

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Abstract

Data analysis especially data with space and time feature in a human-centric way requires interpretable representation of data. With this motivation, we present a granular way of data analysis in which the data and the relationships therein are described through a collection of sets or fuzzy sets (information granules). In this paper, data are described by semantically meaningful descriptors-information granules over the space and time domain. The design process is guided by information granulation and degranulation. Thus a performance index used to obtain the best combination of information granules becomes a crucial issue. The effectiveness of the algorithm is demonstrated by experiments on two kinds of synthetic data and data from Alberta agriculture website.

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Acknowledgments

Support from the Natural Science Foundation of China (NSFC) 61305100 and 61203283, 71401026, the Youth Science Foundation of Communication University of China 3132015XNG1501, YXJS201529, the technology research of cinema management system and collaborative network service platform (2012BAH02F04), National Key Technology Support Program (2013BAH66F02) are gratefully appreciated.

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Authors and Affiliations

  1. School of Computer Science, Communication University of China, Beijing, 100024, China

    Mingli Song & Wenqian Shang

  2. Department of Mathematics, Dalian Maritime University, Dalian, 116026, China

    Lidong Wang

  3. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, T6R 2G7, Canada

    Witold Pedrycz

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  1. Mingli Song
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  2. Wenqian Shang
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  3. Lidong Wang
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  4. Witold Pedrycz
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Correspondence to Mingli Song.

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Song, M., Shang, W., Wang, L. et al. Analysis of spatiotemporal data relationship using information granules. Int. J. Mach. Learn. & Cyber. 8, 1439–1446 (2017). https://doi.org/10.1007/s13042-015-0386-x

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  • DOI: https://doi.org/10.1007/s13042-015-0386-x

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