Granular computing as a basis of human–data interaction: a cognitive cities use case
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Bargiela A, Pedrycz W (2003) Granular computing: an introduction, Springer international series in engineering and computer science, vol 717. Springer, New York
Bargiela A, Pedrycz W (2008) Toward a theory of granular computing for human-centered information processing. Fuzzy Syst IEEE Trans 16(2):320–330
Batyrshin I, Sheremetov L, Zadeh LA (eds) (2007) Perception-based data mining and decision making in economics and finance, studies in computational intelligence, vol 36. Springer, Berlin, Heidelberg
Buyong TB, Frank AU, Kuhn W (1991) A conceptual model of measurement-based multipurpose cadastral systems. J Urban Reg Inf Syst Assoc URISA 3(2):35–49
Cafaro F (2012) Using embodied allegories to design gesture suites for human-data interaction. In: Proceedings of the 2012 ACM conference on ubiquitous computing, UbiComp ’12. ACM, New York, pp 560–563
Crabtree A, Mortier R (2015) Human data interaction: Historical lessons from social studies and cscw. In: Proceedings of the European conference on computer supported cooperative work (ECSCW)
Dempster AP (1967) Upper and lower probabilities induced by a multivalued mapping. Ann Math Stat 38(2):325–339
Dubois D, Prade H (2001) Possibility theory, probability theory and multiple-valued logics: a clarification. Ann Math Artif Intell 32(1–4):35–66
Egenhofer M, Mark D (1995) Naive geography. In: Frank A, Kuhn W (eds) Spatial information theory a theoretical basis for GIS, lecture notes in computer science, vol 988. Springer, Berlin, Heidelberg, pp 1–15
Engelbart D (1962) Augmenting human intellect: a conceptual framework. Sri summary report afosr-3223, Air Force Office of Scientific Research, Washington DC Prepared for: Director of Information Sciences, Contract AF 49(638)-1024, SRI Project No. 3578 (AUGMENT, 3906)
Fine TL (1977) Review: Glenn shafer, a mathematical theory of evidence. Bull Am Math Soc 83(4):667–672
Fogliaroni P, Hobel H (2015) Implementing naive geography via qualitative spatial relation queries. In: Proceedings of the 18th AGILE international conference on geographic information science
Gerla G (2001) Fuzzy logic—mathematical tools for approximate reasoning, trends in logic, vol 11. Springer, Dordrecht
Godo L, Rodríguez RO (2008) Logical approaches to fuzzy similarity-based reasoning: an overview. Number 504. Springer, pp 75–128
Gross R, Acquisti A (2005) Information revelation and privacy in online social networks. In Proceedings of the 2005 ACM workshop on privacy in the Electronic Society, WPES ’05. ACM, New York, pp 71–80
Haddadi H, Mortier R, McAuley D, Crowcroft J (2013) Human-data interaction. Technical report 837, National Science Foundation workshop report
Hayes PJ (1979) The naive physics manifesto. In: Michie D (ed) Expert systems in the electronic age. Edinburgh University Press, Edinburgh, pp 242–270
Hobbs JR (1985) Granularity. In: Proceedings of ninth international joint conference on artificial intelligence. Morgan Kaufmann, Los Angeles, pp 432–435
Kacprzyk J (2015) Computational intelligence and soft computing: closely related but not the same. In: Seising R, Méndez LA (eds) Accuracy and fuzzyness–a life in science and politics. A Festschrift book to Enric Trillas Ruiz. Springer, New York
Kaufmann MA, Portmann E (2015) Biomimetics in design-oriented information systems research. In: Donnellan B, Gleasure R, Helfert M, Kenneally J, Rothenberger M, Trembalay MC, Vandereer D, Winter R (eds) At the vanguard of design science: first impressions and early findings from ongoing research research-in-progress papers and poster presentations from the 10th international conference (DESRIST 2015), pp 53–60
Kee KF, Browning LD, Ballard DI (2012) B. C. E. sociomaterial processes, long term planning, and infrastructure funding: towards effective collaboration and collaboration tools for visual and data analytics. In: NSF sponsored science of interaction for data and visual analytics workshop, Austin, TX, March 2012
Kelly J, Hamm S (2013) Smart machines: IBM’s Watson and the era of cognitive computing. Columbia Business School Publishing, New York
Korolova A (2012) Protecting privacy when mining and sharing user data. Ph.D. thesis, Stanford University
Kreinovich V (2008) Interval computation as an important part of granular computing: an introduction. In: Pedrycz W, Skowron A, Kreinovich V (eds) Handbook of granular computing. Wiley, Chichester, pp 3–31
Krishnamurthy B, Wills CE (2009) On the leakage of personally identifiable information via online social networks. In: Proceedings of the 2Nd ACM workshop on online social networks, WOSN ’09. ACM, New York, pp 7–12
Lakoff G, Núñez RE (2000) Where mathematics comes from: how the embodied mind brings mathematics into being. Basic Books, New York
Licklider J (1960) Man–computer symbiosis. In: IRE transactions on human factors in electronics, HFE:4–10, March 1960
Ligozat G, Renz J (2004) What is a qualitative calculus? a general framework. In: Zhang C, Guesgen HW, Yeap W-K (eds) PRICAI 2004: Trends in artificial intelligence, lecture notes in computer science, vol 3157. Springer, Berlin, Heidelberg, pp 53–64
Lin T (2003) Granular computing. In: Wang G, Liu Q, Yao Y, Skowron A (eds) Rough sets, fuzzy sets, data mining, and granular computing, lecture notes in computer science, vol 2639. Springer, Berlin, Heidelberg, pp 16–24
McAuley D, Mortier R, Goulding J (2011) The dataware manifesto. In: 2011 third international conference on communication systems and networks (COMSNETS), pp 1–6, Jan 2011
Mendel J, Zadeh LA, Trillas E, Yager R, Lawry J, Hagras H, Guadarrama S (2010) What computing with words means to me [discussion forum]. Comput Intell Mag IEEE 5(1):20–26
Mortier R, Haddadi H, Henderson T, McAuley D, Crowcroft J (2014) Human-data interaction: the human face of the data-driven society. CoRR arXiv:abs/1412.6159
Moyser R (2013) Planning for smart cities in the UK. http://www.burohappold.com/blog/post/planning-for-smart-cities-in-the-uk-2179 . Accessed 17 Apr 2014
Mulkar-Mehta R, Hobbs J, Hovy E (2011) Granularity in natural language discourse. In: Proceedings of the ninth international conference on computational semantics, IWCS ’11. Association for Computational Linguistics, Stroudsburg, pp 360–364
Noy N, McGuinness D (eds) (2013) Research Challenges and Opportunities in Knowledge Representation, Final Workshop Report of the NFS Workshop in Arlington VA, USA, Feb 7–8, 2013, Wright State University, Computer Science and Engineering Faculty Publications. http://krnsfworkshop.cs.illinois.edu/final-workshop-report . Accessed 12 Feb 2012
Novák V, Perfilieva I, Močkoř J (1999) Mathematical Principles of Fuzzy Logic. The Kluwer International series in engineering and computer science, series vol 517. Kluwer Academic Publishers, Boston, Dordrecht, London
Pawlak Z (1981) Rough sets. Research report PAS 431, Institute of Computer Science, Polish Academy of Sciences
Pedrycz W (1998) Shadowed sets: representing and processing fuzzy sets. Syst Man Cybern Part B: Cybern IEEE Trans 28(1):103–109
Pedrycz W (2001) Granular computing: an emerging paradigm. Studies in fuzziness and soft computing. Physica Heidelberg, New York
Pedrycz W (2006) Granular computing: an overview. In: Abraham A, de Baets B, K/”ppen M, Nickolay B (eds) Applied soft computing technologies: the challenge of complexity, advances in soft computing, vol 34. Springer, Berlin, Heidelberg, pp 19–34
Pedrycz W (2015) History of mathematics, encyclopedia of life support systems (EOLSS), chapter history and development of granular computing. Number ISBN: 978-1-84826-671-1. Accessed 24 July 2015
Pedrycz W, Skowron A, Kreinovich V (2008) Handbook of granular computing. Wiley-Interscience, New York
Perkal J (1956) On epsilon length. Bulletin de l’Academie Polonaise des Sciences 4:399–403
Perkal J (1966) On the length of empirical curves. Discussion paper no. 10, 1966. Michigan Inter-University Community of Mathematical Geographers, Ann Arbor
Peucker TK (1975) A theory of the cartographic line. In: Proceedings of Auto-Carto II held in Reston, Virginia, on 21–25 September 1975, Falls Church, Virginia: American Congress on Surveying and Mapping, p 508
Portmann E (2013) The FORA framework. A fuzzy grassroots ontology for online reputation management. Springer, Berlin, Heidelberg
Portmann E, Finger M (2016) What are cognitive cities? In: Portmann E, Finger M (eds) Towards cognitive cities: advances in cognitive computing and its applications to the governance of large urban systems. Springer, Berlin (submitted)
Portmann E, Kaufmann M, Graf C (2012) A distributed, semiotic-inductive, and human-oriented approach to web-scale knowledge retrieval. In: Proceedings of the 2012 international workshop on web-scale knowledge representation, retrieval and reasoning. ACM, New York
Randell DA, Cui Z, Cohn AG (1992) A spatial logic based on regions and connection. In: Proceedings 3rd international conference on knowledge representation and reasoning
Roberts FS (1973) Tolerance geometry. NDJFAM 14(1):68–76 (af copy)
Rosenfeld A (1994) Fuzzy plane geometry: triangles. In: Fuzzy systems. IEEE World congress on computational intelligence, vol 2, pp 891–893
Salesin D, Stolfi J, Guibas L (1989) Epsilon geometry: building robust algorithms from imprecise computations. In: SCG ’89: Proceedings of the fifth annual symposium on computational geometry. ACM, New York, pp 208–217
Shi W (1998) A generic statistical approach for modelling error of geometric features in GIS. Int J Geogr Inf Sci 12(2):131–143
Shi W (2009) Principles of modeling uncertainties in spatial data and spatial analyses. CRC Press Inc, Boca Raton
Shi W, Liu W (2000) A stochastic process-based model for the positional error of line segments in gis. Int J Geogr Inf Sci 14(1):51–66
Shi W, Cheung CK, Zhu C (2003) Modelling error propagation in vector-based buffer analysis. Int J Geogr Inf Sci 17(3):251–271
Siemens G (2006) Knowing knowledge. Lulu - Online Self Publishing Book & eBook Company (November 5, 2006)
Wilke G (2009) Approximate geometric reasoning with extended geographic objects. In: Proceedings of the ISPRS COST-workshop on quality, scale and analysis aspects of city models, Lund, Sweden
Wilke G (2012) Towards approximate tolerance geometry for gis—a framework for formalizing sound geometric reasoning under positional tolerance. Ph.D. thesis, Vienna University of Technology
Wilke G (2015) Granular geometry. In: Seising R, Trillas E, Kacprzyk J (eds) Towards the future of fuzzy logic, studies in fuzziness and soft computing, vol 325. Springer International Publishing, Switzerland, pp 79–115
Wilke G, Frank A (2010a) On equality of points and lines. In: GIScience 2010, Zürich, Switzerland
Wilke G, Frank A (2010b) Tolerance geometry—euclids first postulate for points and lines with extensionref306. In: Proceedings of the ACM SIGSPATIAL 2010, San Jose, California, USA
Wilke G, Frank AU (2010c) Tolerance geometry: euclid’s first postulate for points and lines with extension. In: 18th ACM SIGSPATIAL international symposium on advances in geographic information systems, ACM-GIS 2010, 3–5 Nov 2010, San Jose, CA, USA, Proceedings, pp 162–171
Yao Y (2004) A partition model of granular computing. In: Peters JF, Skowron A, Grzymała Busse JW, Kostek B, Świniarski RW, Szczuka M (eds) Transactions on rough sets I, lecture notes in computer science, vol 3100. Springer, Berlin, Heidelberg, pp 232–253
Zadeh LA (1992) Fuzzy logic and the calculus of fuzzy if-then rules. In: Proceedings of the twenty-second international symposium on multiple-valued logic, p 480, May 1992
Zadeh L (1997) Towards a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic. Fuzzy Sets Syst 19:111–127
Zadeh L (2002) Toward a perception-based theory of probabilistic reasoning with imprecise probabilities. In: Grzegorzewski P, Hryniewicz O, Gil M (eds) Soft methods in probability, statistics and data analysis, advances in intelligent and soft computing, vol 16. Physica-Verlag HD, pp 27–61
Zadeh LA (2007) Granular computing—computing with uncertain, imprecise and partially true data. In: Online Proceedings of the international symposium on spatial data quality, June 2007