research-article

Generalized difference method for generating integrated hypotheses in social big data

Authors:

Hiroshi Ishikawa,

Masaharu HirotaAuthors Info & Claims

MEDES '18: Proceedings of the 10th International Conference on Management of Digital EcoSystems

Pages 13 - 22

https://doi.org/10.1145/3281375.3281404

Published: 25 September 2018 Publication History

Abstract

Recently there is strong demand for analytic methodology as to generation of integrated hypotheses for applications involving different sources of social big data. In this paper, first, we introduce an abstract data model for integrating data management and data mining by using mathematical concepts of families, collections of sets to facilitate reproducibility and accountability required for social big data applications. Next, we propose generalized difference methods as a methodology for integrated analysis based on different sources of data. Finally, we validate our proposal by applying it to three use cases by using our data model as their description.

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Cited By

Ishikawa HIshikawa H(2024)Hypothesis Generation by DifferenceHypothesis Generation and Interpretation10.1007/978-3-031-43540-9_6(203-278)Online publication date: 1-Jan-2024
https://doi.org/10.1007/978-3-031-43540-9_6
Ishikawa HYamamoto Y(2021)Social Big Data: Concepts and TheoryTransactions on Large-Scale Data- and Knowledge-Centered Systems XLVII10.1007/978-3-662-62919-2_3(51-79)Online publication date: 17-Jan-2021
https://doi.org/10.1007/978-3-662-62919-2_3
Ishikawa HKato DEndo MHirota MChbeir RManolopoulos YIlarri SPapadopoulos A(2019)Applications of Generalized Difference Method for Hypothesis Generation to Social Big Data in Concept and Real SpacesProceedings of the 11th International Conference on Management of Digital EcoSystems10.1145/3297662.3365822(44-55)Online publication date: 12-Nov-2019
https://dl.acm.org/doi/10.1145/3297662.3365822

Index Terms

Generalized difference method for generating integrated hypotheses in social big data
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis
      1. Modeling methodologies

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cover image ACM Other conferences

MEDES '18: Proceedings of the 10th International Conference on Management of Digital EcoSystems

September 2018

253 pages

ISBN:9781450356220

DOI:10.1145/3281375

Conference Chairs:
Richard Chbeir,
Hiroshi Ishikawa,
Program Chairs:
Kazutoshi Sumiya,
Kenji Hatano,
Mario Koeppen

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 September 2018

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MEDES '18

MEDES '18: The 10th International Conference on Management of Digital EcoSystems

September 25 - 28, 2018

Tokyo, Japan

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MEDES '18 Paper Acceptance Rate 29 of 77 submissions, 38%;

Overall Acceptance Rate 267 of 682 submissions, 39%

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Cited By

Ishikawa HIshikawa H(2024)Hypothesis Generation by DifferenceHypothesis Generation and Interpretation10.1007/978-3-031-43540-9_6(203-278)Online publication date: 1-Jan-2024
https://doi.org/10.1007/978-3-031-43540-9_6
Ishikawa HYamamoto Y(2021)Social Big Data: Concepts and TheoryTransactions on Large-Scale Data- and Knowledge-Centered Systems XLVII10.1007/978-3-662-62919-2_3(51-79)Online publication date: 17-Jan-2021
https://doi.org/10.1007/978-3-662-62919-2_3
Ishikawa HKato DEndo MHirota MChbeir RManolopoulos YIlarri SPapadopoulos A(2019)Applications of Generalized Difference Method for Hypothesis Generation to Social Big Data in Concept and Real SpacesProceedings of the 11th International Conference on Management of Digital EcoSystems10.1145/3297662.3365822(44-55)Online publication date: 12-Nov-2019
https://dl.acm.org/doi/10.1145/3297662.3365822

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