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Emerging, Collective Intelligence for Personal, Organisational and Social Use

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Next Generation Data Technologies for Collective Computational Intelligence

Part of the book series: Studies in Computational Intelligence ((SCI,volume 352))

Abstract

The main objective of this chapter is to present novel technologies for exploiting multiple layers of intelligence from user-contributed content, which together constitute Collective Intelligence, a form of intelligence that emerges from the collaboration and competition among many individuals, and that seemingly has a mind of its own. User contributed content is analysed by integrating research and development in media analysis, mass content processing, user feedback, social analysis and knowledge management to automatically extract the hidden intelligence and make it accessible to end users and organisations. The exploitation of the emerging Collective Intelligence results is showcased in two distinct case studies: an Emergency Response and a Consumers Social Group case study.

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References

  1. The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, Cambridge (2003)

    Google Scholar 

  2. Multiple Bernoulli relevance models for image and video annotation, vol. 2 (2004), http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1315274

  3. Iptc, eventml (2008), http://iptc.org/

  4. Wikipedia in Action: Ontological Knowledge in Text Categorization, doi:10.1109/ICSC 2008.53 (2008)

    Google Scholar 

  5. Aims: Atlas incident management system (2010), http://www.atlasops.com/products/aims.php

  6. Dopplr (2010), http://www.dopplr.com/

  7. Emergency command system (2010), http://www.emergencycommandsystem.com

  8. Fixmystreet (2010), http://www.fixmystreet.com/

  9. ispot, your place to share nature (2010), http://ispot.org.uk/

  10. Mit center for collective intelligence, distributed collaboration project (2010), http://cci.mit.edu/research/collaboration.html

  11. Mobnotes (2010), http://www.mobnotes.com/

  12. Owl 2 web ontology language (2010), http://www.w3.org/TR/owl2-overview/

  13. The protege ontology editor and knowledge acquisition system (2010), http://protege.stanford.edu/

  14. Using geography can help you to meet your flood management responsibilities (2010), http://bit.ly/fc3GQX

  15. Weknowit project deliverable d7.5.1: Consumer and emergency response use case first evaluation report (2010), http://www.weknowit.eu/deliverables

  16. Anderson, A.H.: A comparison of two privacy policy languages: Epal and xacml. In: Proceedings of the 3rd ACM Workshop on Secure Web Services, SWS 2006, pp. 53–60. ACM, New York (2006), doi:http://doi.acm.org/10.1145/1180367.1180378

    Chapter  Google Scholar 

  17. Avrithis, Y., Kalantidis, Y., Tolias, G., Spyrou, E.: Retrieving landmark and non-landmark images from community photo collections. In: Proceedings of the International Conference on Multimedia, MM 2010, pp. 153–162. ACM, New York (2010), doi:10.1145/1873951.1873973

    Chapter  Google Scholar 

  18. Begelman, G., Keller, P., Smadja, F.: Automated Tag Clustering: Improving search and exploration in the tag space (2006), http://www.pui.ch/phred/automated_tag_clustering/

  19. Bloehdorn, S., Hotho, A.: Text classification by boosting weak learners based on terms and concepts. In: Proceedings of the Fourth IEEE International Conference on Data Mining, ICDM 2004, pp. 331–334. IEEE Computer Society, Washington, DC, USA (2004)

    Chapter  Google Scholar 

  20. Brooks, C.H., Montanez, N.: Improved annotation of the blogosphere via autotagging and hierarchical clustering. In: Proceedings of the 15th International Conference on World Wide Web, WWW 2006, pp. 625–632. ACM, New York (2006), doi:http://doi.acm.org/10.1145/1135777.1135869

    Chapter  Google Scholar 

  21. Chang, E., Goh, K., Sychay, G., Wu, G.: Cbsa: Content-based soft annotation for multimodal image retrieval using bayes point machines. IEEE Transactions on Circuits and Systems for Video Technology 13, 26–38 (2003)

    Article  Google Scholar 

  22. Chum, O., Philbin, J., Zisserman, A.: Near Duplicate Image Detection: min-Hash and tf-idf Weighting. In ACM British Machine Vision Conference 2, 1

    Google Scholar 

  23. Clauset, A., Newman, M.E.J., Moore, C.: Finding community structure in very large networks (2004), doi:10.1103/PhysRevE.70.066111

    Google Scholar 

  24. Deerwester, S., Dumais, S.T., Furnas, G.W., Landauer, T.K., Harshman, R.: Indexing by latent semantic analysis. Journal of the American Society for Information Science 41(6), 391–407 (1990)

    Article  Google Scholar 

  25. Doerr, M., Ore, C.E., Stead, S.: The cidoc conceptual reference model: a new standard for knowledge sharing. In: Tutorials, Posters, Panels and Industrial Contributions at the 26th International Conference on Conceptual Modeling. ER 2007, vol. 83, pp. 51–56. Australian Computer Society, Inc, Darlinghurst (2007)

    Google Scholar 

  26. Ekin, A., Tekalp, A.M., Mehrotra, R.: Integrated semantic-syntactic video modeling for search and browsing. IEEE Transactions on Multimedia 6, 839 (2004)

    Article  Google Scholar 

  27. Ferraiolo, D.F., Kuhn, D.R., Chandramouli, R.: Role-Based Access Control. Artech House, Inc., Norwood (2003)

    MATH  Google Scholar 

  28. Fischler, M.A., Bolles, R.C.: Chap. Random Sample Consensus: a Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. In: Readings in computer vision: issues, problems, principles, and paradigms, pp. 726–740. Morgan Kaufmann Publishers Inc, San Francisco (1987)

    Google Scholar 

  29. Francois, A.R., Nevatia, R., Hobbs, J., Bolles, R.C.: Verl: An ontology framework for representing and annotating video events. IEEE Multimedia 12, 76–86 (2005), doi:http://doi.ieeecomputersociety.org/10.1109/MMUL.2005.87

    Article  Google Scholar 

  30. Franke, M., Geyer-Schulz, A.: An update algorithm for restricted random walk clustering for dynamic data sets. Advances in Data Analysis and Classification 3(1), 63–92 (2009)

    Article  MATH  MathSciNet  Google Scholar 

  31. Gabrilovich, E., Markovitch, S.: Overcoming the brittleness bottleneck using wikipedia: enhancing text categorization with encyclopedic knowledge. In: Proceedings of the 21st National Conference on Artificial Intelligence, vol. 2, pp. 1301–1306. AAAI Press, Menlo Park (2006)

    Google Scholar 

  32. Geyer-Schulz, A., Ovelgoenne, M., Sonnenbichler, A.: Getting Help In A Crowd - A Social Emergency Alert Service. In: International Conference on e-Business 2010 (ICETE ICE-B), Athens, Greece, pp. 207–218 (2010)

    Google Scholar 

  33. Geyer-Schulz, A., Thede, A.: Implementation of hierarchical authorization for a web based digital library. In: 3rd International Conference on Cybernetics and Information Technologies, Systems, and Applications, pp. 139–144 (2006)

    Google Scholar 

  34. Giannakidou, E., Koutsonikola, V., Vakali, A., Kompatsiaris, Y.: Co-clustering tags and social data sources. In: The Ninth International Conference on Web-Age Information Management WAIM 2008, pp. 317–324 (2008), doi:10.1109/WAIM.2008.61

    Google Scholar 

  35. Girardin, F., Calabrese, F., Fiore, F.D., Ratti, C., Blat, J.: Digital footprinting: Uncovering tourists with user-generated content. IEEE Pervasive Computing 7, 36–43 (2008), doi:10.1109/MPRV.2008.71

    Article  Google Scholar 

  36. Grauman, K.: Pyramid match hashing: Sub-linear time indexing over partial correspondences. In: CVPR (2007)

    Google Scholar 

  37. Hollenstein, L., Purves, R.: Exploring place through user-generated content: Using Flickr to describe city cores. Journal of Spatial Information Science 1(1), 21–48 (2010)

    Google Scholar 

  38. Janik, M., Kochut, K.: Training-less Ontology-based Text Categorization. In: Workshop on Exploiting Semantic Annotations in Information Retrieval (ESAIR 2008) at the 30th European Conference on Information Retrieval, ECIR 2008 (2008)

    Google Scholar 

  39. Jegou, H., Douze, M., Schmid, C.: Hamming embedding and weak geometric consistency for large scale image search. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part I. LNCS, vol. 5302, pp. 304–317. Springer, Heidelberg (2008), http://dx.doi.org/10.1007/978-3-540-88682-2_24

    Chapter  Google Scholar 

  40. Jeon, J., Lavrenko, V., Manmatha, R.: Automatic image annotation and retrieval using cross-media relevance models (2003)

    Google Scholar 

  41. Kalantidis, Y., Tolias, G., Avrithis, Y., Phinikettos, M., Spyrou, E., Mylonas, P., Kollias, S.: Viral: Visual image retrieval and localization. Multimedia Tools and Applications, 1–38 (2010), doi:10.1007/s11042-010-0651-7

    Google Scholar 

  42. Kalantidis, Y., Tolias, G., Spyrou, E., Mylonas, P., Avrithis, Y.: Visual image retrieval and localization. In: 7th International Workshop on Content-Based Multimedia Indexing, Greece (2009)

    Google Scholar 

  43. Kemp, C., Shafto, P., Berke, A., Tenenbaum, J.B.: Combining causal and similarity-based reasoning. nips (2006)

    Google Scholar 

  44. Kennedy, L., Naaman, M., Ahern, S., Nair, R., Rattenbury, T.: How flickr helps us make sense of the world: context and content in community-contributed media collections. In: Proceedings of the 15th International Conference on Multimedia, MULTIMEDIA 2007, pp. 631–640. ACM, New York (2007), doi:http://doi.acm.org/10.1145/1291233.1291384

    Chapter  Google Scholar 

  45. Kleinberg, J.M.: Authoritative sources in a hyperlinked environment. J. ACM 46, 604–632 (1999), doi:http://doi.acm.org/10.1145/324133.324140

    Article  MATH  MathSciNet  Google Scholar 

  46. Lewis, D.: Naive (bayes) at forty: The independence assumption in information retrieval. In: Nédellec, C., Rouveirol, C. (eds.) ECML 1998. LNCS, vol. 1398, pp. 4–15. Springer, Heidelberg (1998), doi:10.1007/BFb0026666

    Chapter  Google Scholar 

  47. Lewis, D.D., Yang, Y., Rose, T.G., Li, F.: Rcv1: A new benchmark collection for text categorization research. J. Mach. Learn. Res. 5, 361–397 (2004)

    Google Scholar 

  48. Li, J., Wang, J.Z.: Automatic linguistic indexing of pictures by a statistical modeling approach. IEEE Trans. Pattern Anal. Mach. Intell. 25, 1075–1088 (2003), doi:10.1109/TPAMI.2003.1227984

    Article  Google Scholar 

  49. Liu, D., Hua, X.S., Wang, M., Zhang, H.J.: Retagging social images based on visual and semantic consistency. In: Proceedings of the 19th International Conference on World Wide Web, WWW 2010, pp. 1149–1150. ACM, New York (2010), doi:http://doi.acm.org/10.1145/1772690.1772848

    Chapter  Google Scholar 

  50. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60, 91–110 (2004), doi:10.1023/B:VISI.0000029664.99615.94

    Article  Google Scholar 

  51. Luo, F., Wang, J.Z., Promislow, E.: Exploring local community structures in large networks. In: Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2006, pp. 233–239. IEEE Computer Society, Washington, DC,USA (2006), doi:http://dx.doi.org/10.1109/WI.2006.72

    Chapter  Google Scholar 

  52. MacQueen, J.B.: Some methods for classification and analysis of multivariate observations. In: Le Cam, L.M., Neyman, J. (eds.) Proc. of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281–297. University of California Press, Berkeley (1967)

    Google Scholar 

  53. Malone, T.W., Klein, M.: Harnessing collective intelligence to address global climate change. Innovations: Technology, Governance, Globalization 2(3), 15–26 (2007), doi:10.1162/itgg.2007.2.3.15

    Article  Google Scholar 

  54. Mccallum, A.K.: BOW: A toolkit for statistical language modeling, text retrieval, classification and clustering (1996), http://www.cs.cmu.edu/~mccallum/bow/

  55. Mika, P.: Ontologies are us: A unified model of social networks and semantics. In: International Semantic Web Conference, pp. 522–536 (2005)

    Google Scholar 

  56. Mueller, E.T.: Chapter 17 event calculus. In: van Harmelen, V.L.F., Porter, B. (eds.) Handbook of Knowledge Representation. Foundations of Artificial Intelligence, vol. 3, pp. 671–708. Elsevier, Amsterdam (2008), doi:10.1016/S1574-6526(07)03017-9

    Google Scholar 

  57. Newman, M.E.J., Girvan, M.: Finding and evaluating community structure in networks. Phys. Rev. E 69(2), 026,113 (2004), doi:10.1103/PhysRevE.69.026113

    Article  Google Scholar 

  58. Niste’r, D., Stewe’nius, H.: Scalable recognition with a vocabulary tree. In: CVPR, pp. 2161–2168 (2006)

    Google Scholar 

  59. Ovelgoenne, M., Geyer-Schulz, A., Stein, M.: A randomized greedy modularity clustering algorithm for community detection in huge social networks. In: 4th International Workshop on Social Network Analysis and Mining (SNA-KDD 2010), Washington, DC, USA (2010)

    Google Scholar 

  60. Ovelgoenne, M., Sonnenbichler, A.C., Geyer-Schulz, A.: Social emergency alert service - a location-based privacy-aware personal safety service. In: Proceedings of the 2010 Fourth International Conference on Next Generation Mobile Applications, Services and Technologies, NGMAST 2010, pp. 84–89. IEEE Computer Society, Washington, DC, USA (2010), doi:http://dx.doi.org/10.1109/NGMAST.2010.27

    Chapter  Google Scholar 

  61. Papadopoulos, S., Kompatsiaris, Y., Vakali, A.: A graph-based clustering scheme for identifying related tags in folksonomies. In: Bach Pedersen, T., Mohania, M.K., Tjoa, A.M. (eds.) DAWAK 2010. LNCS, vol. 6263, pp. 65–76. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  62. Papadopoulos, S., Vakali, A., Kompatsiaris, Y.: Community detection in collaborative tagging systems. In: Pardede, E. (ed.) Community-built Database: Research and Development. Springer, Heidelberg (2010)

    Google Scholar 

  63. Papadopoulos, S., Zigkolis, C., Tolias, G., Kalantidis, Y., Mylonas, P., Kompatsiaris, Y., Vakali, A.: Image clustering through community detection on hybrid image similarity graphs. In: 2010 International Conference on Image Processing (ICIP 2010), Hong-Kong, September 26-29 (2010)

    Google Scholar 

  64. Philbin, J., Chum, O., Isard, M., Sivic, J., Zisserman, A.: Object retrieval with large vocabularies and fast spatial matching. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2007, pp. 1–8 (2007)

    Google Scholar 

  65. Prelec, D.: A Bayesian Truth Serum for Subjective Data. Science 306(5695), 462–466 (2004), doi:10.1126/science.1102081

    Article  Google Scholar 

  66. Quack, T., Leibe, B., Van Gool, L.: World-scale mining of objects and events from community photo collections. In: Proceedings of the 2008 International Conference on Content-based Image and Video Retrieval, CIVR 2008, pp. 47–56. ACM, New York (2008), doi:http://doi.acm.org/10.1145/1386352.1386363

    Chapter  Google Scholar 

  67. Raghavan, U.N., Albert, R., Kumara, S.: Near linear time algorithm to detect community structures in large-scale networks. Physical Review E 76(3), 036,106 (2007), doi:10.1103/PhysRevE.76.036106

    Article  Google Scholar 

  68. Raimond, Y., Abdallah, S.: The event ontology (October 2007), http://motools.sf.net/event

  69. Rissanen, E.: Extensible access control markup language (xacml) version 3.0 committee draft 03 (2010), http://docs.oasis-open.org/xacml/3.0/ xacml-3.0-core-spec-cd-03-en.pdf

  70. Saathoff, C., Scherp, A.: Unlocking the semantics of multimedia presentations in the web with the multimedia metadata ontology. In: Proceedings of the 19th International Conference on World Wide Web, WWW 2010, pp. 831–840. ACM, New York (2010), doi:http://doi.acm.org/10.1145/1772690.1772775

    Chapter  Google Scholar 

  71. Sandhu, R.S., Samarati, P.: Access control: Principles and practice. IEEE Communications Magazine 32, 40–48 (1994)

    Article  Google Scholar 

  72. Schenk, S., Saathoff, C., Staab, S., Scherp, A.: Semaplorer-interactive semantic exploration of data and media based on a federated cloud infrastructure. Web Semant. 7, 298–304 (2009), doi:10.1016/j.websem.2009.09.006

    Article  Google Scholar 

  73. Scherp, A., Franz, T., Saathoff, C., Staab, S.: F–a model of events based on the foundational ontology dolce+dns ultralight. In: Proceedings of the Fifth International Conference on Knowledge Capture, K-CAP 2009, pp. 137–144. ACM, New York (2009), doi:http://doi.acm.org/10.1145/1597735.1597760

    Chapter  Google Scholar 

  74. Sikkel, K.: A group-based authorization model for cooperative systems. In: Proceedings of the Fifth Conference on European Conference on Computer-Supported Cooperative Work, pp. 345–360. Kluwer Academic Publishers, Norwell (1997)

    Google Scholar 

  75. Sivic, J., Zisserman, A.: Video Google: A Text Retrieval Approach to Object Matching in Videos. In: IEEE International Conference on Computer Vision, vol. 2, pp. 1470–1477 (2003), doi:10.1109/ICCV.2003.1238663

    Google Scholar 

  76. Torres, L.H.: Citizen sourcing in the public interest. Knowledge Management for Development Journal 3(1), 134–145 (2007)

    Google Scholar 

  77. Vapnik, V.N.: The nature of statistical learning theory. Springer-Verlag New York, Inc., New York (1995)

    MATH  Google Scholar 

  78. C. Wang, F. Jing, L. Zhang, H.-J. Zhang: Content-based image annotation refinement. In: CVPR (2007)

    Google Scholar 

  79. Wang, X.j., Mamadgi, S., Thekdi, A., Kelliher, A., Sundaram, H.: Eventory – an event based media repository. In: Proceedings of the International Conference on Semantic Computing, pp. 95–104. IEEE Computer Society, Washington, DC, USA (2007), doi:10.1109/ICSC.2007.33

    Chapter  Google Scholar 

  80. Westermann, U., Jain, R.: Toward a common event model for multimedia applications. IEEE MultiMedia 14, 19–29 (2007), doi:10.1109/MMUL.2007.23

    Article  Google Scholar 

  81. Winerman, L.: Social networking: Crisis communication. Nature 457(7228), 376 (2009), doi:10.1038/457376a

    Article  Google Scholar 

  82. Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Morgan Kaufmann Series in Data Management Systems. Morgan Kaufmann, San Francisco (2005), http://bit.ly/ihBvSG

    Google Scholar 

  83. Wolfson, H.J., Rigoutsos, I.: Geometric hashing: an overview. IEEE Computational Science and Engineering 4(4), 10–21 (1997), doi:10.1109/99.641604

    Article  Google Scholar 

  84. Work, D.B., Blandin, S., Tossavainen, O.P., Piccoli, B., Bayen, A.M.: A Traffic Model for Velocity Data Assimilation. Applied Mathematics Research Express 2010(1), 1–35 (2010), doi:10.1093/amrx/abq002

    Google Scholar 

  85. Xu, X., Yuruk, N., Feng, Z., Schweiger, T.A.J.: Scan: a structural clustering algorithm for networks. In: KDD 2007: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 824–833. ACM, New York (2007)

    Chapter  Google Scholar 

  86. Zhou, D., Bousquet, O., Lal, T.N., Weston, J., Schölkopf, B.: Learning with local and global consistency. Advances in Neural Information Processing Systems 16 (2004)

    Google Scholar 

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Authors and Affiliations

  1. Informatics & Telematics Institute, Thermi, Thessaloniki, Greece

    Sotiris Diplaris, Symeon Papadopoulos & Yiannis Kompatsiaris

  2. Karlsruhe Institute of Technology, Germany

    Andreas Sonnenbichler & Michael Ovelgoenne

  3. Software Mind S.A., Krakow, Poland

    Tomasz Kaczanowski

  4. National Technical University of Athens, Greece

    Phivos Mylonas

  5. University of Koblenz-Landau, Germany

    Ansgar Scherp & Maciej Janik

  6. Department of Computer Science, Aristotle University of Thessaloniki, Greece

    Symeon Papadopoulos

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  1. Sotiris Diplaris
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  1. School of Computing & Maths, University of Derby, DE22 1GB, Derby, United Kingdom (UK)

    Nik Bessis

  2. Dept de Llenguatges i Sistemes Informàtics, Universitat Politècnica de Catalunya, Barcelona, Spain

    Fatos Xhafa

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Diplaris, S. et al. (2011). Emerging, Collective Intelligence for Personal, Organisational and Social Use. In: Bessis, N., Xhafa, F. (eds) Next Generation Data Technologies for Collective Computational Intelligence. Studies in Computational Intelligence, vol 352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20344-2_20

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