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Swarm Intelligence in Data Mining pp 153–189Cite as

Data and Text Mining with Hierarchical Clustering Ants

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 34))

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References

  1. Kumar, R., Raghavan, P., Rajagopalan, S., Tomkins, A. (2001) On semi-automated web taxonomy construction. In: Proceedings of the Fourth International Workshop on the Web and Databases (WebDB), Santa Barbara

    Google Scholar 

  2. Sanderson, M., Croft, W.B. (1999) Deriving concept hierarchies from text. In: Research and Development in Information Retrieval 206-213

    Google Scholar 

  3. McCallum, A.K., Nigam, K., Rennie, J., Seymore, K. (2000) Automating the construction of internet portals with machine learning. Information Retrieval 3: 127-163

    Article  Google Scholar 

  4. Goss, S., Deneubourg, J.L. (1991) Harvesting by a group of robots. In F.Varela, P.Bourgine, eds. Proceedings of the First European Conference on Artificial Life, Paris, France, Elsevier Publishing. 195-204

    Google Scholar 

  5. Lumer, E., Faieta, B. (1994) Diversity and adaptation in populations of clustering ants. In Cliff, D., Husbands, P., Meyer, J. W. S., eds.: Proceedings of the Third International Conference on Simulation of Adaptive Behavior, MIT Press, Cambridge, Massachusetts. 501-508

    Google Scholar 

  6. Deneubourg, J.L., Goss, S., Franks, N., Sendova-Franks, A., Detrain, C., Chretien, L. (1990) The dynamics of collective sorting: robot-like ant and ant-like robots. In: Proceedings of the First International Conference on Simulation of Adaptive Behavior. 356-365

    Google Scholar 

  7. Kuntz, P., Layzell, P., Snyers, D. (1997) A colony of ant-like agents for partitioning in vlsi technology. In Husbands, P., Harvey, I., eds.: Proceedings of the Fourth European Conference on Artificial Life. 417-424

    Google Scholar 

  8. Kuntz, P., Snyers, D., Layzell, P.J. (1998) A stochastic heuristic for visualising graph clusters in a bi-dimensional space prior to partitioning. J. Heuristics 5 327-351

    Article  Google Scholar 

  9. Abraham, A., Ramos, V. (2003) Web usage mining using artificial ant colony clustering and linear genetic programming. In: The Congress on Evolutionary Computation, Canberra, Australia, IEEE-Press. 1384-1391

    Chapter  Google Scholar 

  10. Handl, J., Knowles, J., Dorigo, M. (2003) On the performance of ant-based clustering. 204-213

    Google Scholar 

  11. N. Labroche, C. Guinot (2004) Fast unsupervised clustering with artificial ants. In: Proceedings of the Parallel Problem Solving from Nature (PPSN VIII), Birmingham, England. 1143-1152

    Google Scholar 

  12. Anderson, C., Theraulaz, G., Deneubourg, J. (2002) Self-assemblages in insect societies. Insectes Sociaux 49 99-110

    Article  Google Scholar 

  13. Lioni, A., Sauwens, C., Theraulaz, G., Deneubourg, J.L. (2001) The dynamics of chain formation in oecophylla longinoda. Journal of Insect Behavior 14 679-696

    Article  Google Scholar 

  14. Theraulaz, G., Bonabeau, E., Sauwens, C., Deneubourg, J.L., Lioni, A., Libert, F., Passera, L., Sol é , R.V. (2001) Model of droplet formation and dynamics in the argentine ant (linepithema humile mayr). Bulletin of Mathematical Biology

    Google Scholar 

  15. Colorni, A., Dorigo, M., Maniezzo, V. (1991) Distributed optimization by ant colonies. In F.Varela, P.Bourgine, eds.: Proceedings of the First European Conference on Artificial Life, Paris, France, Elsevier Publishing. 134-142

    Google Scholar 

  16. Roux, O., Fonlupt, C. (2000) Ant programming: Or how to use ants for automatic programming. From Ant Colonies to Artificial Ants: 2nd International Workshop on Ant Colony Optimization

    Google Scholar 

  17. Bianchi, L., Gambardella, L.M., Dorigo, M. (2002) An ant colony optimization approach to the probabilistic traveling salesman problem. In: Proceedings of PPSN-VII, Seventh International Conference on Parallel Problem Solving from Nature. Lecture Notes in Computer Science, Springer Verlag, Berlin, Germany

    Google Scholar 

  18. Ando, S., Iba, H. (2002) Ant algorithm for construction of evolutionary tree. In Langdon, W.B., ed.: GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, New York, Morgan Kaufmann Publishers. 131

    Google Scholar 

  19. Murata, S., Kurokawa, H., Kokaji, S. (1994). In: IEEE International Conference on Robotics and Automation. 441-448

    Google Scholar 

  20. Pamecha, A., Ebert-Uphoff, I., Chirikjian, G. (1997) Useful metrics for modular robot motion planning

    Google Scholar 

  21. Murata, S., Yoshida, E., Kamimura, A., Kurokawa, H., Tomita, K., Kokaji, S. (2002) M-tran: Self-reconfigurable modular robotic system. IEEE/ASME Transactions on Mechatronics 431-441

    Google Scholar 

  22. Jorgensen, M.W., Ostergaard, E.H., Lund, H.H. (2004) Modular atron: Modules for a self-reconfigurable robot. In: IEEE/RSJ InternationalConference on Intelligent Robots and Systems (IROS). 2068-2073

    Google Scholar 

  23. Mondada, F., Pettinaro, G.C., Guignard, A., Kwee, I.W., Floreano, D., Deneubourg, J.L., Nolfi, S., Gambardella, L.M., Dorigo, M. (2004) Swarm-bot: A new distributed robotic concept. Auton. Robots 17 193-221

    Article  Google Scholar 

  24. Azzag, H., Guinot, C., Oliver, A., Venturini, G. (2005) A hierarchical ant based clustering algorithm and its use in three real-world applications. In Wout Dullaert, Marc Sevaux, K.S., Springael, J., eds.: European Journal of Operational Research (EJOR). Special Issue on Applications of Metaheuristics.

    Google Scholar 

  25. Eiben, A.E., Hinterding, R., Michalewicz, Z. (1999) Parameter control in evolutionary algorithms. IEEE Trans. on Evolutionary Computation 3 124-141

    Article  Google Scholar 

  26. Blake, C., Merz, C. (1998) UCI repository of machine learning databases

    Google Scholar 

  27. Guinot, C., Malvy, D.J.M., Morizot, F., Tenenhaus, M., Latreille, J., Lopez, S., Tschachler, E., Dubertret, L. (2003) Classification of healthy human facial skin. Textbook of Cosmetic Dermatology Third edition

    Google Scholar 

  28. Fowlkes, E.B., Mallows, C.L. (1983) A method for comparing two hierarchical clusterings. J. American Statistical Associationn 78 553-569

    Article  MATH  Google Scholar 

  29. Jain, A., Dubes, R. (1988) Algorithms for Clustering Data. Prentice Hall Advanced Reference Series

    Google Scholar 

  30. Monmarch é , N. (2000) Algorithme de fourmis artificielles : applications à la classification et à l’optimisation. Th èse de doctorat, Universit é de Tours

    Google Scholar 

  31. Labroche, N. (2003) Mod élisation du syst ème de reconnaissance chimique des fourmis pour le probl ème de la classification non-supervis ée : application à la mesure d’audience sur Internet. Th èse de doctorat, Laboratoire d’Informatique, Universit é de Tours

    Google Scholar 

  32. Han, E.H., Boley, D., Gini, M., Gross, R., Hastings, K., Karypis, G., Kumar, V., Mobasher, B., Moore, J. (1998) Webace: a web agent for document categorization and exploration. In: AGENTS ’98: Proceedings of the second international conference on Autonomous agents, New York, NY, USA, ACM Press (1998) 408-415

    Chapter  Google Scholar 

  33. Filo, D., Yang, J. (1997) Yahoo!

    Google Scholar 

  34. Base de WebKb http://www-2.cs.cmu.edu/ webkb/.

  35. Salton, G., Buckley, C. (1988) Term-weighting approaches in automatic text retrieval. Inf. Process. Manage. 24 513-523

    Article  Google Scholar 

  36. Zipf, G.K. (1949) Human behaviour and the principle of least effort. Addison-Wesley, Cambridge, Massachusetts

    Google Scholar 

  37. Salton, G., McGill, M.J. (1983) Introduction to Modern Information Retrieval. McGraw- Hill, Inc., New York, NY

    MATH  Google Scholar 

  38. Cooley, R. (2000) Web Usage Mining: Discovery and Application of Interesting Patterns from Web Data. Ph.d. thesis, University of Minnesota

    Google Scholar 

  39. Azzag, H., Picarougne, F., Guinot, C., Venturini, G. (2005) Vrminer: a tool for multimedia databases mining with virtual reality. In Darmont, J., Boussaid, O., eds.: Processing and Managing Complex Data for Decision Support. to appear.

    Google Scholar 

  40. Johnson, B., Shneiderman, B. (1991) Tree-maps: A space-filling approach to the visualization of hierarchical information structures. In: Proc. of Visualization’91, San Diego, CA 284-291

    Google Scholar 

  41. Shneiderman, B. (1992) Tree visualization with tree-maps: A 2-D space-filling approach. ACM Transactions on Graphics 11 92-99

    Article  MATH  Google Scholar 

  42. Carey, M., Heesch, D.and R üger, S. (2003) Info navigator: A visualization tool for document searching and browsing. In: Proceedings of the 9th International Conference on Distributed Multimedia Systems (DMS’2003)

    Google Scholar 

  43. Robertson, G.G., Mackinlay, J.D., Card, S.K. (1991) Cone trees: animated 3d visualizations of hierarchical information. In: CHI ’91: Proceedings of the SIGCHI conference on Human factors in computing systems, New York, NY, USA, ACM Press. 189-194

    Google Scholar 

  44. Fisher, D.H. (1991) Knowledge Acquisition via Incremental Conceptual Clustering. Machine Learning 2 139-172

    Google Scholar 

  45. Tian, Z., Raghu, R., Miron, L. (1996) Birch: An efficient data clustering method for very large databases. In Jagadish, H.V., Mumick, I.S., eds.: Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data, Montreal, Quebec, Canada, June 4-6, 1996, ACM Press. 103-114

    Google Scholar 

  46. Sudipto, G., Rajeev, R., Kyuseok, S. (1998) CURE: an efficient clustering algorithm for large databases. In Haas, L.M., Tiwary, A., eds.: Proceedings ACM SIGMOD International Conference on Management of Data, Seattle, Washington, USA, ACM Press. 73-84

    Google Scholar 

  47. Domingos, P., Hulten, G. (2001) Catching up with the data: Research issues in mining data streams

    Google Scholar 

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Author information

Authors and Affiliations

  1. Laboratoire d'Informatique, école Polytechnique de l'Université de Tours - Département Informatique, 64, Avenue Jean Portalis, 37200, Tours, France

    Hanene Azzag

  2. C.E.R.I.E.S., 20, rue Victor Noir, 92521, Neuilly sur Seine Cedex

    Christiane Guinot

  3. Laboratoire d'Informatique, école Polytechnique de l'Université de Tours - Département Informatique, 64, Avenue Jean Portalis, 37200, Tours, France

    Gilles Venturini

Authors
  1. Hanene Azzag
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  2. Christiane Guinot
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  3. Gilles Venturini
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Editor information

Editors and Affiliations

  1. IITA Professorship Program, School of Computer Science and Engineering Chung-Ang University, 221 Heukseok-dong, 156-756, Dongjak-gu Seoul, Republic of Korea

    Ajith Abraham

  2. Department of Computer Science, Faculty of Mathematics and Computer Science, Babes-Bolyai University, Cluj-Napoca, Kogalniceanu 1, 400084, Cluj - Napoca, Romania

    Crina Grosan

  3. CVRM-IST, IST, Technical University of Lisbon, Av. Rovisco Pais, 1049-001, Lisboa, Portugal

    Vitorino Ramos

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Azzag, H., Guinot, C., Venturini, G. (2006). Data and Text Mining with Hierarchical Clustering Ants. In: Abraham, A., Grosan, C., Ramos, V. (eds) Swarm Intelligence in Data Mining. Studies in Computational Intelligence, vol 34. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-34956-3_7

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  • DOI: https://doi.org/10.1007/978-3-540-34956-3_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34955-6

  • Online ISBN: 978-3-540-34956-3

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