- Email: [email protected]
Selected insights into building data associations and their granular augmentations
Available online at www.sciencedirect.com
ScienceDirect
Available online at www.sciencedirect.com Procedia Computer Science 00 (2018) 000–000
ScienceDirect
www.elsevier.com/locate/procedia
Procedia Computer Science 120 (2017) 4
9th 9thInternational InternationalConference Conferenceon onTheory Theoryand andApplication Applicationof ofSoft SoftComputing, Computing,Computing Computingwith with Words and Perception, ICSCCW 2017, 24-25 22-23 August August 2017, 2017, Budapest, Budapest, Hungary Hungary
Selected insights into building data associations and their granular augmentations Witold Pedrycz* Department of Electrical & Computer Engineering, University of Alberta, Edmonton AB T6R 2V4 Canada
Abstract Data are the blood life of today’s society. Revealing interpretable and conceptually stable associations (relationships) within data forms one of the central items on the agenda of data analytics. With this regard, associative memories capturing linkages between data positioned in two (or more) data spaces are examples of commonly considered architectures. In contrast to the existing constructs of memories, we propose a new category of architectures that exhibits several essential features: (i) associative mapping is spanned over a collection of prototypes (viz. representatives) of data and in this way becomes focused on their structural essentials, (ii) prototypes are built through a process of collaborative clustering, (iii) the design process retains privacy aspects by not disclosing locally available data, (iv) optimization of bidirectional and multidirectional recall is presented. In the sequel, we demonstrate how granular mappings engaging granular parameter spaces are developed and assessed. Associative relationships constructed in terms of granular bidirectional and multidirectional associative memories are investigated. We also develop granular autoencoders and stacked granular auto encoders offering further support of the development process. © 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 9th International Conference on Theory and Application of Soft Computing, Computing with Words and Perception.
* Corresponding author E-mail address: [email protected] 1877-0509 © 2018 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 9th International Conference on Theory and Application of Soft Computing, Computing with Words and Perception. 1877-0509 © 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 9th International Conference on Theory and application of Soft Computing, Computing with Words and Perception. 10.1016/j.procs.2017.11.200
ScienceDirect
Available online at www.sciencedirect.com Procedia Computer Science 00 (2018) 000–000
ScienceDirect
www.elsevier.com/locate/procedia
Procedia Computer Science 120 (2017) 4
9th 9thInternational InternationalConference Conferenceon onTheory Theoryand andApplication Applicationof ofSoft SoftComputing, Computing,Computing Computingwith with Words and Perception, ICSCCW 2017, 24-25 22-23 August August 2017, 2017, Budapest, Budapest, Hungary Hungary
Selected insights into building data associations and their granular augmentations Witold Pedrycz* Department of Electrical & Computer Engineering, University of Alberta, Edmonton AB T6R 2V4 Canada
Abstract Data are the blood life of today’s society. Revealing interpretable and conceptually stable associations (relationships) within data forms one of the central items on the agenda of data analytics. With this regard, associative memories capturing linkages between data positioned in two (or more) data spaces are examples of commonly considered architectures. In contrast to the existing constructs of memories, we propose a new category of architectures that exhibits several essential features: (i) associative mapping is spanned over a collection of prototypes (viz. representatives) of data and in this way becomes focused on their structural essentials, (ii) prototypes are built through a process of collaborative clustering, (iii) the design process retains privacy aspects by not disclosing locally available data, (iv) optimization of bidirectional and multidirectional recall is presented. In the sequel, we demonstrate how granular mappings engaging granular parameter spaces are developed and assessed. Associative relationships constructed in terms of granular bidirectional and multidirectional associative memories are investigated. We also develop granular autoencoders and stacked granular auto encoders offering further support of the development process. © 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 9th International Conference on Theory and Application of Soft Computing, Computing with Words and Perception.
* Corresponding author E-mail address: [email protected] 1877-0509 © 2018 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 9th International Conference on Theory and Application of Soft Computing, Computing with Words and Perception. 1877-0509 © 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 9th International Conference on Theory and application of Soft Computing, Computing with Words and Perception. 10.1016/j.procs.2017.11.200