Human-Centric Information Processing Through Granular Modelling

1. Front Matter

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2. Rough-Granular Computing in Human-Centric Information Processing

   • Tuan Trung Nguyen, Andrzej Skowron

   Pages 1-30

3. Integrative Levels of Granularity

   • Yiyu Yao

   Pages 31-47

4. Affinities between Perceptual Granules: Foundations and Perspectives

   • James F. Peters, Sheela Ramanna

   Pages 49-66

5. Concept Granular Computing Based on Lattice Theoretic Setting

   • Wen-xiu Zhang, Hong-zhi Yang, Jian-min Ma, Guo-fang Qiu

   Pages 67-94

6. Interpretability of Fuzzy Information Granules

   • Corrado Mencar

   Pages 95-118

7. Semantic Driven Fuzzy Clustering for Human-Centric Information Processing Applications

   • Paulo Fazendeiro, José Valente de Oliveira

   Pages 119-151

8. Many-Valued Logic Tools for Granular Modeling

   • Siegfried Gottwald

   Pages 153-184

9. Type-2 Fuzzy Logic and the Modelling of Uncertainty in Applications

   • Robert John, Simon Coupland

   Pages 185-201

10. Interval Type-2 Fuzzy Logic Applications

    • Oscar Castillo, Patricia Melin

    Pages 203-231

11. Processing of Information Microgranules within an Individual’s Society

    • Bruno Apolloni, Simone Bassis, Antonio G. Zippo

    Pages 233-264

12. Autonomous Composition of Fuzzy Granules in Ambient Intelligence Scenarios

    • Giovanni Acampora, Vincenzo Loia, Athanasios V. Vasilakos

    Pages 265-287

13. Information Processing in Biomedical Applications

    • Nick J. Pizzi

    Pages 289-311

14. Gene Interactions Sub-networks and Soft Computing

    • Ranajit Das, Sushmita Mitra

    Pages 313-327

15. Uncertain Identification Problems in the Context of Granular Computing

    • Tadeusz Burczyński, Piotr Orantek

    Pages 329-350

16. Visualizing Huge Image Databases by Formal Concept Analysis

    • Kazuhito Sawase, Hajime Nobuhara, Barnabas Bede

    Pages 351-373

17. Artificial Dendritic Cells: Multi-faceted Perspectives

    • Julie Greensmith, Uwe Aickelin

    Pages 375-395

18. Back Matter

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Information granules and their processing permeate a way in which we perceive the world, carryout processing at the conceptual (abstract) level, and communicate our findings to the surrounding environment. The importance of information granulation becomes even more apparent when we are faced with a rapidly growing flood of data, become challenged to make decisions in complex data settings and are required to appreciate the context from which the data is derived. Human centricity of systems that claim to be “intelligent” and the granular computing come hand in hand. It is not surprising at all to witness that the paradigm of Granular Computing has started to gain visibility and continues along this path by gathering interest from the circles of academics and practitioners. It is quite remarkable that the spectrum of application and research areas that have adopted information granulation as a successful strategy for dealing with information complexity covers such diverse fields as bioinformatics, image understanding, environmental monitoring, urban sustainability, to mention few most visible in the literature. Undoubtedly, there are two important aspects of Granular Computing that are worth stressing. First, there are several formalisms in which information granules are articulated so be intervals (sets), fuzzy sets, rough sets, soft sets, approximate sets, near sets and alike. They are complementary and each of them offers some interesting views at the complexity of the world and cyberspace.

• Granular Computing
• Granular Modelling
• bioinformatics
• calculus
• computational intelligence
• databases
• fuzzy
• fuzzy logic
• fuzzy set
• fuzzy sets
• intelligence
• linear optimization
• modeling
• uncertainty

• School of Computer Science, The University of Nottingham, Semenyih Selangor Darul Ehsan, Malaysia

  Andrzej Bargiela

• Department of Electrical & Computer Engineering, University of Alberta, Edmonton, Canada

  Witold Pedrycz

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