Introduction of researcher

As of  2009.11.07      

 

[Name] 

HOULE, Michael E.

[Date of birth] 

1962/07/20

[Doctoral degrees] 

PhD McGill University (Canada) 1989

[Affiliation] 

Visiting Professor, National Institute of Informatics, Collaborative Research Unit

Visiting Professor, Graduate University of Advanced Studies (Sokendai), Department of Informatics

[Room] 

1403

[Telephone] 

+81-3-4212-2538

[Facsimile] 

+81-3-3556-1916

[E-mail] 

meh@nii.ac.jp

[Personal home page] 

http://research.nii.ac.jp/~meh/

[Research fields] 

Data mining (search, clustering, classification), design and analysis of algorithms, visualization, combinatorial geometry

 

 

 

 

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Outline of current research

 

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Education

 

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Career

 

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Refereed publications, published books

 

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Patents and other works

 

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Current teaching

 

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Software tools

 

 

 

 

 

 

 

 

[Outline of current research] 

 

Design and analysis of data structures for approximate similarity search in extremely high-dimensional settings.

Local clustering models and techniques for data mining applications (such as data summarization & navigation).

 

[Education] 

 

PhD in Computer Science (computational geometry), McGill University, 1989

BSc (Honours) in Mathematics and Computer Science, McGill University, 1984

 

[Career] 

 

1989-1990  Research Associate, Dept of Communication Engineering, Kyushu University

1990-1992  Research Associate, Dept of Information Science, University of Tokyo

1992-1997  Lecturer, Dept of Computer Science & Software Engineering, University of Newcastle (Australia)

1997-1999  Senior Lecturer

1999-2001  Senior Lecturer, Dept of Computer Science, University of Sydney (Australia)

2001-2003  Visiting Scientist at IBM Tokyo Research Laboratory

2004-  Visiting Professor at the National Institute for Informatics

2009-  Visiting Professor at the Graduate University for Advanced Studies (Sokendai)

 

[Refereed publications, published books] 

 
  1. S. Honiden, M. E. Houle, C. Sommer and M. Wolff. Approximate shortest path queries in graphs using Voronoi duals. Transactions on Computational Science, 2010, to appear (Special Issue on the Best Papers of ISVD 2009).
  2. M. E. Houle, H.-P. Kriegel, P. Kroger, E. Schubert and A. Zimek. Can shared-neighbor distances defeat the curse of dimensionality? In Proc. 22nd International Conference on Scientific and Statistical Database Management (SSDBM 2010), Heidelberg, Germany, June 2010, to appear.
  3. N. X. Vinh and M. E. Houle. A set correlation model for partitional clustering. In Proc. 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2010), Hyderabad, India, June 2010, pp. 4-15.
  4. U. Qasim, V. Oria, B. Wu, T. M. Özsu, and M. E. Houle. A partial-order-based active cache for recommender systems. In Proc. 3rd ACM Conference on Recommender Systems (RecSys 2009), New York, NY, USA, October 2009, pp. 209-212.
  5. S. Honiden, M. E. Houle, and C. Sommer. Balancing graph Voronoi diagrams. In Proc. 6th International Symposium on Voronoi Diagrams (ISVD 2009), Copenhagen, Denmark, June 2009, pp. 183-191.
  6. S. Honiden, M. E. Houle, C. Sommer and M. Wolff. Approximate shortest path queries in graphs using Voronoi duals. In Proc. 6th International Symposium on Voronoi Diagrams (ISVD 2009), Copenhagen, Denmark, June 2009, pp. 53-62.
  7. N. Hervé, N. Boujemaa and M. E. Houle. Document description: what works for images should also work for text? In Proc. 21st IS&T/SPIE Symposium on Electronic Imaging, San Jose, CA, USA, January 2009, paper 7255-11.
  8. M. E. Houle. The relevant-set correlation model for data clustering. Statistical Analysis and Data Mining 1(3):157-176, 2008 (Special Issue on the Best Papers of SDM’08).
  9. M. E. Houle. The relevant-set correlation model for data clustering. In Proc. 8th SIAM International Conference on Data Mining (SDM 2008), Atlanta, GA, USA, April 2008, pp. 775-786.
  10. M. E. Houle and N. Grira. A correlation-based model for unsupervised feature selection. In Proc. 16th ACM Conference on Information and Knowledge Management (CIKM 2007), Lisboa, Portugal, November 2007, pp. 897-900.
  11. D.-D. Le, S. Satoh and M. E. Houle. Boosting face retrieval by using relevant set correlation clustering. In Proc. 8th International Conference on Multimedia & Expo (ICME 2007), Beijing, China, July 2007, pp. 524-527.
  12. N. Grira and M. E. Houle. Best of both: a hybridized centroid-medoid clustering heuristic. In Proc. 24th International Conference on Machine Learning (ICML 2007), Corvallis, OR, USA, June 2007, pp. 313-320.
  13. D.-D. Le, S. Satoh, M. E. Houle and D. P. T. Nguyen. Finding important people in large news video databases using multimodal and clustering analysis. In Proc. 2nd IEEE International Workshop on Multimedia Databases and Data Management (IEEE-MDDM 2007), Istanbul, Turkey, April 2007, pp. 127-136.
  14. M. E. Houle. Clustering without data: the relevant set correlation model. In Proc. International Workshop on Data-Mining and Statistical Science (DMSS 2006), Sapporo, Japan, September 2006, pp. 54-61.
  15. M. E. Houle. Clustering without data: the GreedyRSC heuristic. In Proc. International Workshop on Data-Mining and Statistical Science (DMSS 2006), Sapporo, Japan, September 2006, pp. 62-69.
  16. D.-D. Le, S. Satoh and M. E. Houle. Face retrieval in broadcasting news video by fusing temporal and intensity information. In Proc. 5th Conference on Image and Video Retrieval (CIVR 2006), Tempe AZ, USA, July 2006, pp. 391-400.
  17. M. E. Houle, F. Hurtado, M. Noy and E. Rivera-Campo. Graphs of triangulations and perfect matchings. Graphs and Combinatorics 21(3):325-331, 2005.
  18. M. E. Houle and J. Sakuma. Fast approximate similarity search in extremely high-dimensional data sets. In Proc. 21st IEEE International Conference on Data Engineering (ICDE 2005), Tokyo, Japan, Apr. 2005, pp. 619-630.
  19. M. E. Houle, A. Symvonis and D. R. Wood. Dimension-exchange algorithms for token distribution on tree-connected architectures. J. Parallel and Distributed Computing 64(5):591-605, 2004.
  20. M. E. Houle. Navigating massive data sets via local clustering. In Proc. 9th ACM SIGKDD Conf. on Knowledge Discovery and Data Mining (KDD), Washington DC, USA, Aug. 2003, pp. 547-552.
  21. Y. Morimoto, M. Aono, M. E. Houle and K. S. McCurley. Extracting spatial knowledge from the web. In Proc. 2003 International Symposium on Applications and the Internet (SAINT 2003), Orlando, USA, Jan. 2003, pp. 326-333.
  22. C. Hernando, M. E. Houle and F. Hurtado. On local transformation of polygons with visibility properties. Theoretical Computer Science 289(2):919-937, 2002.
  23. V. Estivill-Castro and M. E. Houle. "Approximating Proximity for Fast and Robust Distance-Based Clustering" in Data Mining: A Heuristic Approach Vol. I, H. A. Abbass, R. Sarkar and C. Newton, eds., Idea Group Publishing, Hershey, PA, pp. 22-46, 2002. (ISBN 1-930708-25-4.)
  24. M. E. Houle, A. Symvonis and D. R. Wood. Dimension-exchange algorithms for load balancing on trees. In Proc. 9th International Colloquium on Structural Information & Communication Complexity (SIROCCO 2002), Andros, Greece, June 2002, Carleton Scientific, pp. 181-196.
  25. P. Bose, M. E. Houle, G. Toussaint. Every set of disjoint line segments admits a binary tree. Discrete & Computational Geometry 26(3):387-410, 2001.
  26. V. Estivill-Castro and M. E. Houle. Robust distance-based clustering with applications to spatial data mining. Algorithmica 30(2):216-242, 2001. (special issue on algorithms for geographical information)
  27. C. Friedrich and M. E. Houle. Graph drawing in motion II. In Lecture Notes in Comp. Sci. 2265 (Proc. 9th Symposium on Graph Drawing (GD 2001), Vienna, Austria), Springer-Verlag, 2001, pp. 220-231.
  28. V. Estivill-Castro and M. E. Houle. Data structures for minimization of total within-group distance for spatio-temporal clustering. In Lecture Notes in Artificial Intelligence 2168 (Proc. 5th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD’01), Freiburg, Germany) Springer-Verlag, 2001, pp. 91-102.
  29. K. Pulo and M. E. Houle. Evaluation of virtual world systems. In Proc. 13th Australian Software Engineering Conference (ASWEC 2001), Canberra, Australia, Aug. 2001, IEEE Computer Society, pp. 98-107.
  30. T. Menzies, J. Powell and M. E. Houle. Fast formal analysis of requirements via topoi diagrams. In Proc. 23rd International Conference on Software Engineering (ICSE 2001), Toronto, Canada, 2001, pp. 391-400.
  31. V. Estivill-Castro and M. E. Houle. Fast randomized algorithms for robust estimation of location. In Lecture Notes in Artificial Intelligence 2007 (Proc. International Workshop on Temporal, Spatial and Spatio-Temporal Data Mining (TSDM 2000), Lyon, France), Springer-Verlag, 2000, pp. 77-88.
  32. C. Hernando, M. E. Houle and F. Hurtado. On local transformation of polygons with visibility properties. In Lecture Notes in Comp. Sci. 1858 (Proc. 6th Annual International Computing and Combinatorics Conference (COCOON’00), Sydney, Australia), Springer-Verlag, 2000, pp. 54-63.
  33. M. E. Houle, E. Tempero, and G. Turner. Optimal dimension-exchange token distribution on complete binary trees. Theoretical Computer Science 220:363-376, 1999.
  34. B. K. Bhattacharya and M. E. Houle. Generalized maximum independent sets for trees in subquadratic time. In Lecture Notes in Comp. Sci. 1741 (Proc. 10th International Symposium on Algorithms and Computation (ISAAC’99), Chennai, India), Springer-Verlag, 1999, pp. 435-445.
  35. V. Estivill-Castro and M. E. Houle. Robust clustering of large geo-referenced data sets. In Lecture Notes in Comp. Sci. 1574 (Proc. 3rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’99), Beijing), Springer-Verlag, 1999, pp. 327-337.
  36. V. Estivill-Castro and M. E. Houle. Robust clustering of large data sets with categorical attributes. In Australian Computer Science Communications 21(2) (Proc. 10th Australasian Database Conference ADC’99, Auckland, New Zealand), Springer-Verlag, 1999, pp. 165-176.
  37. P. Bose, H. Everett, S. Fekete, M. E. Houle, A. Lubiw, H. Meijer, K. Romanik, G. Rote, T. C. Shermer, S. Whitesides and C. Zelle. A visibility representation for graphs in three dimensions. J. Graph Algorithms and Applications 2(3):1-16, 1998.
  38. M. E. Houle and G. Turner. Dimension-exchange token distribution on the mesh and the torus. Parallel Computing 24(2):247-265, 1998.
  39. M. E. Houle and R. Webber. Approximation algorithms for finding best viewpoints. In Lecture Notes in Comp. Sci. 1547 (Proc. 6th Symposium on Graph Drawing (GD 1998), Montreal, Canada), Springer-Verlag, 1998, pp. 210-223.
  40. S. Fekete, M. E. Houle and S. Whitesides. The wobbly logic engine: proving hardness of non-rigid geometric graph representation problems. In Lecture Notes in Comp. Sci. 1353 (Proc. 5th Symposium on Graph Drawing (GD 1997), Rome, Italy), Springer-Verlag, 1998, pp. 272-283.
  41. P. Eades, M. E. Houle and R. Webber. Finding best viewpoints for three-dimensional graph drawings. In Lecture Notes in Comp. Sci. 1353 (Proc. 5th Symposium on Graph Drawing (GD 1997), Rome, Italy), Springer-Verlag, 1998, pp. 87-98.
  42. M. E. Houle and Simon. Social and ethical education in computing using virtual environments. In Proc. 2nd Australasian Comput. Sci. Educ. Conf., Melbourne, Australia, July 1997, pp. 24-31.
  43. M. E. Houle and Simon. Ethics, programming, and virtual environments. In Proc. ACM SIGCSE/CUE Conf. Integrating Technology into Comput. Sci. Educ., Uppsala, Sweden, June 1997, pp. 91-93.
  44. B. K. Bhattacharya and M. E. Houle. Generalized maximum independent sets for trees. In Proc. Computing: the Australasian Theory Symposium (CATS’97), Sydney, Australia, Feb. 1997, pp. 17-25.
  45. M. E. Houle and G. Turner. Dimension-exchange token distribution on the mesh and the torus. In Lecture Notes in Comp. Sci. 1178 (Proc. 7th International Symposium on Algorithms and Computation (ISAAC’96), Osaka, Japan), Springer-Verlag, 1996, pp. 233-232.
  46. M. E. Houle. On local transformations of simple polygons. Australian Computer Science Communications 18(3), (Proceedings of Computing: the Australasian Theory Symposium (CATS’96), Melbourne, Australia), Jan. 1996, pp. 64-71.
  47. D. Avis and M. E. Houle. Computational aspects of Helly’s theorem and its relatives. International Journal of Computational Geom. & Appl. 5(4):357-367, 1995.
  48. S. P. Fekete, M. E. Houle, S. Whitesides. New results on a visibility representation of graphs in 3D. In Lecture Notes in Comp. Sci. 1027 (Proc. 3rd Symposium on Graph Drawing (GD 1995), Passau, Germany), Springer-Verlag, 1995, pp. 234-241.
  49. P. Bose, M. E. Houle, G. Toussaint. Every set of disjoint line segments admits a binary tree. In Lecture Notes in Comp. Sci. 834 (Proc. 5th International Symposium on Algorithms and Computation (ISAAC’94), Beijing, P. R. China), Springer-Verlag, 1994, pp. 20-28.
  50. G.-H. Chen, M. E. Houle and M.-T. Kuo. The Steiner problem in distributed computing systems. Information Sciences 74(1):73-96, 1993.
  51. M. E. Houle. Algorithms for weak and wide separation of sets. Discrete Appl. Math. 45(2):139-159, 1993.
  52. M. E. Houle, H. Imai, K. Imai, J.-M. Robert and P. Yamamoto. Orthogonal weighted linear L1 and L∞ approximation and applications. Discrete Appl. Math. 43(3):217-232, 1993.
  53. H. ElGindy, M. E. Houle, W. Lenhart, M. Miller, D. Rappaport and S. Whitesides. Dominance drawings of bipartite graphs. In Proc. 5th Canadian Conf. on Comput. Geom., Waterloo, Canada, Aug. 1993, pp. 187-191.
  54. M. E. Houle. Theorems on the existence of separating surfaces. Discrete & Computational Geometry 6(1):49-56, 1991.
  55. D. Avis and M. E. Houle. Computational aspects of Helly’s theorem and its relatives. In Proc. 3rd Canadian Conf. on Comput. Geom., Vancouver, Canada, Aug. 1991, pp. 11-14.
  56. Te. Asano, M. E. Houle, H. Imai, and K. Imai. Linear-space solutions to hashing-related geometric minimax problems. In Proc. 2nd Canadian Conf. on Comput. Geom., Ottawa, Canada, Aug. 1990, pp. 20-23.
  57. M. E. Houle. Algorithms for weak and wide separation of sets. In Proc. International Workshop on Disc. Alg. and Complexity, Fukuoka, Japan, Nov. 1989, pp. 61-68.
  58. M. E. Houle and G. T. Toussaint. Computing the width of a set. IEEE Trans. Patt. Anal. Mach. Intell. 10(5):761-765, 1988.
  59. M. E. Houle, H. Imai, K. Imai and J.-M. Robert. Weighted orthogonal linear L∞-approximation and applications. In Lecture Notes in Comp. Sci. 382 (Proc. 1989 Workshop on Algorithms and Data Structures, Carleton Univ., Ottawa, Canada), Springer-Verlag, 1989, pp. 183-191.
  60. M. E. Houle and G. T. Toussaint. Computing the width of a set. In Proc. 1st ACM Symposium on Computational Geometry (SoCG 1985), Baltimore, MD, USA, 1985, pp. 1-7.

[Patents and other works] 

 
  1. J. Sakuma and M. E. Houle. Selection of elements strongly related to a predetermined reference element. United States Patent 7492971, awarded 17 February 2009. Japanese Patent 4070211, awarded 25 January 2008. (Applications of the SASH data structure [15].)
  2. M. E. Houle. Computer system, method, and program product for generating a data structure for information retrieval, and an associated graphical user interface. United States Patent 7428541, awarded 23 September 2008. Japanese Patent 3974511, awarded 22 June 2007. (The PatClust clustering method, introduced in [17].)
  3. M. Aono, M. E. Houle and M. Kobayashi. Information processing using a hierarchy structure of randomized samples. United States Patent 7216129, awarded 8 May 2007. Japanese Patent 3860046, awarded 29 September 2006. (The SASH data structure for approximate similarity search, introduced in [15].)
  4. M. E. Houle. Evaluation and cluster formation based on element correlation. United States Patent Application 20050251514, published 10 November 2005. Japanese Patent Application JP2005-301786, published 27 October 2005.
  5. M. Aono, M. E. Houle and M. Kobayashi. Computer executable dimension reduction and retrieval engine. United States Patent Application 20050027678, published 3 February 2005. Japanese Patent 4074564, awarded 1 February 2008.

[Current teaching] 

 

Courses taught:

[Software tools] 

 

Software tools based on my research at NII are available for download:

  • M. E. Houle. The SASH approximate similarity search structure (2006). (the SASH page)
  • M. E. Houle. GreedyRSC clustering tool (2009). (the RSC page)