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Exploring Message Correlation in Crowd-Based Data Using Hyper Coordinates Visualization Technique

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Predictive Econometrics and Big Data (TES 2018)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 753))

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Abstract

Analytical exploration for necessary information and insights from heterogeneous and multivariate dataset is challenging in visual analytics research due to the complexity of data and tasks. One of the data analytics target is to examine the relationship in the dataset, such as considering how the data elements and subsets are connected together. This work takes into account the direct and indirect connection relations: elements and subsets of elements might not only be directly linked together, but also possibly be indirectly associated via the relationships from other elements/subsets as well. Stream of messages instantly put on the cyberspace from the crowd is an example for such kind of dataset. In this paper, we present an approach to estimate the correlation between streaming messages collection in terms of large scale data processing, whilst the Hyper Coordinates visualization technique is designed to support those correlations exploration. The prototype tool is built to demonstrate the concepts for crowd-based data in the financial market domain.

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Notes

  1. 1.

    https://sentifi.com.

  2. 2.

    We define here a binary relationship between two tables, i.e., we pick one attribute up from each table to make a relationship. In real database, a relationship may be created from several attributes. However, we can transform them into a single attribute by specifying representative identifier.

  3. 3.

    http://spark.apache.org/graphx/.

  4. 4.

    https://d3js.org/.

  5. 5.

    http://jquery.com/.

  6. 6.

    http://getbootstrap.com/.

  7. 7.

    http://fontawesome.io/.

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Acknowledgment

The authors would like to thank Quang M. Le and Tuan A. Ta at Sentifi AG (Ho Chi Minh City office, Vietnam) for their supports and discussions on working scenario.

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Authors and Affiliations

  1. School of Engineering, Tan Tao University, Duc Hoa, Long An, Vietnam

    Tien-Dung Cao, Dinh-Quyen Nguyen & Hien Duy Tran

Authors
  1. Tien-Dung Cao
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  2. Dinh-Quyen Nguyen
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  3. Hien Duy Tran
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Correspondence to Tien-Dung Cao .

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Editors and Affiliations

  1. Computer Science Department, University of Texas at El Paso, El Paso, Texas, USA

    Vladik Kreinovich

  2. International College, Chiang Mai University, Chiang Mai, Thailand

    Songsak Sriboonchitta

  3. International College, Chiang Mai University, Chiang Mai, Thailand

    Nopasit Chakpitak

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Cao, TD., Nguyen, DQ., Tran, H.D. (2018). Exploring Message Correlation in Crowd-Based Data Using Hyper Coordinates Visualization Technique. In: Kreinovich, V., Sriboonchitta, S., Chakpitak, N. (eds) Predictive Econometrics and Big Data. TES 2018. Studies in Computational Intelligence, vol 753. Springer, Cham. https://doi.org/10.1007/978-3-319-70942-0_5

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  • DOI: https://doi.org/10.1007/978-3-319-70942-0_5

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