The SCEAS System
Navigation Menu

Search the dblp DataBase

Title:
Author:

Shusaku Tsumoto: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Shusaku Tsumoto, Hiroshi Tanaka
    Induction of Expert System Rules from Clinical Databases Based on Rough Set Theory and Resampling Methods. [Citation Graph (0, 0)][DBLP]
    AIME, 1995, pp:399-400 [Conf]
  2. Shusaku Tsumoto, Hiroshi Tanaka, Hiromi Amano, Kimie Ohyama, Takayuki Kuroda
    COBRA: Integration of Knowledge-Bases with Case-Databases in the Domain of Congenital Malformation. [Citation Graph (0, 0)][DBLP]
    AIME, 1995, pp:393-394 [Conf]
  3. Shusaku Tsumoto, Hiroshi Tanaka
    Algebraic Specification of Empirical Inductive Learning Methods based on Rough Sets and Matroid Theory. [Citation Graph (0, 0)][DBLP]
    AISMC, 1994, pp:224-243 [Conf]
  4. Shusaku Tsumoto, Hiroshi Tanaka
    Induction of Probabilistic Rules Based on Rough Set Theory. [Citation Graph (0, 0)][DBLP]
    ALT, 1993, pp:410-423 [Conf]
  5. Shoji Hirano, Shusaku Tsumoto
    Empirical Comparison of Clustering Methods for Long Time-Series Databases. [Citation Graph (0, 0)][DBLP]
    Active Mining, 2003, pp:268-286 [Conf]
  6. Shusaku Tsumoto, Takahira Yamaguchi, Masayuki Numao, Hiroshi Motoda
    Active Mining Project: Overview. [Citation Graph (0, 0)][DBLP]
    Active Mining, 2003, pp:1-10 [Conf]
  7. Shoji Hirano, Xiaoguang Sun, Shusaku Tsumoto
    On Similarity Measures for Cluster Analysis in Clinical Laboratory Examination Databases. [Citation Graph (0, 0)][DBLP]
    COMPSAC, 2002, pp:1170-1175 [Conf]
  8. Shoji Hirano, Shusaku Tsumoto
    A Knowledge-Oriented Clustering Technique Based on Rough Sets. [Citation Graph (0, 0)][DBLP]
    COMPSAC, 2001, pp:632-637 [Conf]
  9. Shusaku Tsumoto
    Problems with Mining Medical Data. [Citation Graph (0, 0)][DBLP]
    COMPSAC, 2000, pp:467-468 [Conf]
  10. Shusaku Tsumoto
    Rule and Matroid Theory. [Citation Graph (0, 0)][DBLP]
    COMPSAC, 2002, pp:1176-1181 [Conf]
  11. Shusaku Tsumoto, Shoji Hirano, Eisuke Hanada
    Internet-based Decision Support: Towards E-Hospital. [Citation Graph (0, 0)][DBLP]
    COMPSAC, 2003, pp:595-600 [Conf]
  12. Shusaku Tsumoto, Tsau Young Lin, James F. Peters
    Foundations of Data Mining via Granular and Rough Computing. [Citation Graph (0, 0)][DBLP]
    COMPSAC, 2002, pp:1123-1124 [Conf]
  13. Shusaku Tsumoto
    Data Structure and Algorithm in Data Mining: Granular Computing View. [Citation Graph (0, 0)][DBLP]
    COMPSAC (1), 2006, pp:26-27 [Conf]
  14. Shusaku Tsumoto
    Discovery of Positive and Negative Knowledge in Medical Databases Using Rough Sets. [Citation Graph (0, 0)][DBLP]
    Progress in Discovery Science, 2002, pp:543-552 [Conf]
  15. Shoji Hirano, Xiaoguang Sun, Shusaku Tsumoto
    Analysis of Time-series Medical Databases Using Multiscale Structure Matching and Rough Sets-based. [Citation Graph (0, 0)][DBLP]
    FUZZ-IEEE, 2001, pp:1547-1550 [Conf]
  16. Shusaku Tsumoto
    Medical Diagnostic Rules As Upper Approximation of Rough Sets. [Citation Graph (0, 0)][DBLP]
    FUZZ-IEEE, 2001, pp:1551-1554 [Conf]
  17. Hidenao Abe, Miho Ohsaki, Shusaku Tsumoto, Takahira Yamaguchi
    Evaluating a Rule Evaluation Support Method with Learning Models Based on Objective Rule Evaluation Indices - A Case Study with a Meningitis Data Mining Result. [Citation Graph (0, 0)][DBLP]
    HIS, 2005, pp:169-174 [Conf]
  18. Shoji Hirano, Shusaku Tsumoto
    Grouping of Soccer Game Records by Multiscale Comparison Technique and Rough Clustering. [Citation Graph (0, 0)][DBLP]
    HIS, 2005, pp:399-404 [Conf]
  19. Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
    A Rule Evaluation Support Method with Learning Models Based on Objective Rule Evaluation Indexes. [Citation Graph (0, 0)][DBLP]
    ICDM, 2005, pp:549-552 [Conf]
  20. Shoji Hirano, Shusaku Tsumoto
    Indiscernibility Degree of Objects for Evaluating Simplicity of Knowledge in the Clustering Procedure. [Citation Graph (0, 0)][DBLP]
    ICDM, 2001, pp:211-217 [Conf]
  21. Shoji Hirano, Shusaku Tsumoto
    Mining Similar Temporal Patterns in Long Time-Series Data and Its Application to Medicine. [Citation Graph (0, 0)][DBLP]
    ICDM, 2002, pp:219-226 [Conf]
  22. Shusaku Tsumoto, Shoji Hirano
    Visualization of Rule's Similarity using Multidimensional Scaling. [Citation Graph (0, 0)][DBLP]
    ICDM, 2003, pp:339-346 [Conf]
  23. Shusaku Tsumoto, Shoji Hirano
    Pattern Discovery based on Rule Induction and Taxonomy Generation. [Citation Graph (0, 0)][DBLP]
    ICDM, 2003, pp:661-664 [Conf]
  24. Shoji Hirano, Shusaku Tsumoto
    Cluster Analysis of Time-Series Medical Data Based on the Trajectory Representation and Multiscale Comparison Techniques. [Citation Graph (0, 0)][DBLP]
    ICDM, 2006, pp:896-901 [Conf]
  25. Shusaku Tsumoto, Kimiko Matsuoka, Shigeki Yokoyama
    Risk Mining in Hospital Information Systems. [Citation Graph (0, 0)][DBLP]
    ICDM Workshops, 2006, pp:699-704 [Conf]
  26. Shusaku Tsumoto, Shoji Hirano
    Residual Matrix and Statistical Independence in a Contingency Table. [Citation Graph (0, 0)][DBLP]
    ICDM Workshops, 2006, pp:433-437 [Conf]
  27. Miho Ohsaki, Hidenao Abe, Shusaku Tsumoto, Hideto Yokoi, Takahira Yamaguchi
    Proposal of Medical KDD Support User Interface Utilizing Rule Interestingness Measures. [Citation Graph (0, 0)][DBLP]
    ICDM Workshops, 2006, pp:759-764 [Conf]
  28. Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
    Evaluating Learning Algorithms Composed by a Constructive Meta-Learning Scheme for a Rule Evaluation Support Method. [Citation Graph (0, 0)][DBLP]
    ICDM Workshops, 2006, pp:305-310 [Conf]
  29. Shoji Hirano, Shusaku Tsumoto
    Indiscernibility-Based Clustering: Rough Clustering. [Citation Graph (0, 0)][DBLP]
    IFSA, 2003, pp:378-386 [Conf]
  30. Shusaku Tsumoto
    Mining Multi-level Diagnostic Process Rules from Clinical Databases Using Rough Sets and Medical Diagnostic Model. [Citation Graph (0, 0)][DBLP]
    IFSA, 2003, pp:362-369 [Conf]
  31. Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
    Evaluating Learning Algorithms for a Rule Evaluation Support Method Based on Objective Rule Evaluation Indices. [Citation Graph (0, 0)][DBLP]
    ISMIS, 2006, pp:379-388 [Conf]
  32. Shoji Hirano, Shusaku Tsumoto
    Empirical Evaluation of Dissimilarity Measures for Time-Series Multiscale Matching. [Citation Graph (0, 0)][DBLP]
    ISMIS, 2003, pp:454-462 [Conf]
  33. Shoji Hirano, Shusaku Tsumoto
    Clustering Time-Series Medical Databases Based on the Improved Multiscale Matching. [Citation Graph (0, 0)][DBLP]
    ISMIS, 2005, pp:612-621 [Conf]
  34. Shoji Hirano, Shusaku Tsumoto
    Characteristics of Indiscernibility Degree in Rough Clustering Examined Using Perfect Initial Equivalence Relations. [Citation Graph (0, 0)][DBLP]
    ISMIS, 2006, pp:454-462 [Conf]
  35. Shusaku Tsumoto
    Discovery of Clinical Knowledge in Hospital Information Systems: Two Case Studies. [Citation Graph (0, 0)][DBLP]
    ISMIS, 2000, pp:573-581 [Conf]
  36. Shusaku Tsumoto
    Automated Discovery of Decision Rule Chains Using Rough Sets and Medical Diagnostic Model. [Citation Graph (0, 0)][DBLP]
    ISMIS, 2002, pp:321-332 [Conf]
  37. Shusaku Tsumoto
    Mining Diagnostic Rules with Taxonomy from Medical Databases. [Citation Graph (0, 0)][DBLP]
    ISMIS, 2003, pp:40-48 [Conf]
  38. Shusaku Tsumoto
    Statistical Independence from the Viewpoint of Linear Algebra. [Citation Graph (0, 0)][DBLP]
    ISMIS, 2005, pp:56-64 [Conf]
  39. Shusaku Tsumoto
    Induction of Positive and Negative Deterministic Rules based on Rough Set Model. [Citation Graph (0, 0)][DBLP]
    ISMIS, 1997, pp:298-307 [Conf]
  40. Shusaku Tsumoto
    Knowledge Discovery in Clinical Databases: An Experiment with Rule Induction and Statistics. [Citation Graph (0, 0)][DBLP]
    ISMIS, 1999, pp:349-357 [Conf]
  41. Shusaku Tsumoto, Shoji Hirano
    Visualization of Similarities and Dissimilarities in Rules Using Multidimensional Scaling. [Citation Graph (0, 0)][DBLP]
    ISMIS, 2005, pp:38-46 [Conf]
  42. Shusaku Tsumoto, Hiroshi Tanaka
    Induction of Expert System Rules from Databases Based on Rough Set Theory and Resampling Methods. [Citation Graph (0, 0)][DBLP]
    ISMIS, 1996, pp:128-138 [Conf]
  43. Shusaku Tsumoto, Wojciech Ziarko
    The Application of Rough Sets-Based Data Mining Technique to Differential Diagnosis of Meningoenchepahlitis. [Citation Graph (0, 0)][DBLP]
    ISMIS, 1996, pp:438-447 [Conf]
  44. Shusaku Tsumoto, Shoji Hirano, Akira Yasuda, Kouhei Tsumoto
    Analysis of Amino Acid Sequences by Statistical Technique. [Citation Graph (0, 0)][DBLP]
    JCIS, 2002, pp:1169-1173 [Conf]
  45. Shoji Hirano, Shusaku Tsumoto
    On Constructing Clusters from Non-Euclidean Dissimilarity Matrix by Using Rough Clustering. [Citation Graph (0, 0)][DBLP]
    JSAI Workshops, 2005, pp:5-16 [Conf]
  46. Shoji Hirano, Shusaku Tsumoto, Tomohiro Okuzaki, Yutaka Hata
    A Clustering Method for Nominal and Numerical Data Based on Rough Set Theory. [Citation Graph (0, 0)][DBLP]
    JSAI Workshops, 2001, pp:400-405 [Conf]
  47. Shusaku Tsumoto, Shoji Hirano, Masahiro Inuiguchi
    Workshop on Rough Set Theory and Granular Computing - Summary. [Citation Graph (0, 0)][DBLP]
    JSAI Workshops, 2001, pp:239- [Conf]
  48. Shusaku Tsumoto, Takashi Washio
    Risk Mining - Overview. [Citation Graph (0, 0)][DBLP]
    JSAI, 2006, pp:303-304 [Conf]
  49. Shusaku Tsumoto, Hiroshi Tanaka
    Selection of Probabilistic Measure Estimation Method Based on Recursive Iteration of Resampling Methods. [Citation Graph (0, 0)][DBLP]
    KDD Workshop, 1994, pp:121-132 [Conf]
  50. Shusaku Tsumoto, Hiroshi Tanaka
    Automated Selection of Rule Induction Methods Based on Recursive Iteration of Resampling Methods and Multiple Statistical Testing. [Citation Graph (0, 0)][DBLP]
    KDD, 1995, pp:312-317 [Conf]
  51. Shusaku Tsumoto, Hiroshi Tanaka
    Automated Discovery of Functional Components of Proteins from Amino-Acid Sequences Based on Rough Sets and Change of Representation. [Citation Graph (0, 0)][DBLP]
    KDD, 1995, pp:318-324 [Conf]
  52. Shusaku Tsumoto, Hiroshi Tanaka
    Automated Discovery of Medical Expert System Rules from Clinical Databases Based on Rough Sets. [Citation Graph (0, 0)][DBLP]
    KDD, 1996, pp:63-69 [Conf]
  53. Yasushi Matsumura, Takashi Matsunaga, Yusuke Maeda, Shusaku Tsumoto, Hiroshi Matsumura, Michio Kimura
    Consultation System for Diagnosis of Headache and Facial Pain: "RHINOS". [Citation Graph (0, 0)][DBLP]
    LP, 1985, pp:287-298 [Conf]
  54. Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
    Evaluating Model Construction Methods with Objective Rule Evaluation Indices to Support Human Experts. [Citation Graph (0, 0)][DBLP]
    MDAI, 2006, pp:93-104 [Conf]
  55. Shusaku Tsumoto
    Mining Diagnostic Taxonomy Using Interval-Based Similarity from Clinical Databases. [Citation Graph (0, 0)][DBLP]
    MDAI, 2004, pp:115-126 [Conf]
  56. Shusaku Tsumoto, Shoji Hirano
    A Comparative Study of Clustering Methods for Long Time-Series Medical Databases. [Citation Graph (0, 0)][DBLP]
    MDAI, 2004, pp:260-272 [Conf]
  57. Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
    Evaluating a Rule Evaluation Support Method Based on Objective Rule Evaluation Indices. [Citation Graph (0, 0)][DBLP]
    PAKDD, 2006, pp:509-519 [Conf]
  58. Shoji Hirano, Tomohiro Okuzaki, Yutaka Hata, Shusaku Tsumoto, Kouhei Tsumoto
    A Rough Set-Based Clustering Method with Modification of Equivalence Relations. [Citation Graph (0, 0)][DBLP]
    PAKDD, 2001, pp:507-512 [Conf]
  59. Shoji Hirano, Shusaku Tsumoto
    Dealing with Relative Similarity in Clustering: An Indiscernibility Based Approach. [Citation Graph (0, 0)][DBLP]
    PAKDD, 2003, pp:513-518 [Conf]
  60. Andrzej Skowron, Jaroslaw Stepaniuk, Shusaku Tsumoto
    Information Granules for Spatial Reasoning. [Citation Graph (0, 0)][DBLP]
    PAKDD, 2000, pp:380-383 [Conf]
  61. Einoshin Suzuki, Shusaku Tsumoto
    Evaluating Hypothesis-Driven Exception-Rule Discovery with Medical Data Sets. [Citation Graph (0, 0)][DBLP]
    PAKDD, 2000, pp:208-211 [Conf]
  62. Shusaku Tsumoto
    Automated Discovery of Plausible Rules Based on Rough Sets and Rough Inclusion. [Citation Graph (0, 0)][DBLP]
    PAKDD, 1999, pp:210-219 [Conf]
  63. Shusaku Tsumoto
    Rule Discovery in Databases with Missing Values Based on Rough Set Model. [Citation Graph (0, 0)][DBLP]
    PAKDD, 1999, pp:274-278 [Conf]
  64. Shoji Hirano, Shusaku Tsumoto
    Multiscale Comparison of Temporal Patternsin Time-Series Medical Databases. [Citation Graph (0, 0)][DBLP]
    PKDD, 2002, pp:188-199 [Conf]
  65. Shoji Hirano, Shusaku Tsumoto
    An Indiscernibility-Based Clustering Method with Iterative Refinement of Equivalence Relations. [Citation Graph (0, 0)][DBLP]
    PKDD, 2003, pp:192-203 [Conf]
  66. Shoji Hirano, Shusaku Tsumoto
    Finding Interesting Pass Patterns from Soccer Game Records. [Citation Graph (0, 0)][DBLP]
    PKDD, 2004, pp:209-218 [Conf]
  67. Shinsuke Sugaya, Einoshin Suzuki, Shusaku Tsumoto
    Support Vector Machines for Knowledge Discovery. [Citation Graph (0, 0)][DBLP]
    PKDD, 1999, pp:561-567 [Conf]
  68. Shusaku Tsumoto
    Clinical Knowledge Discovery in Hospital Information Systems: Two Case Studies. [Citation Graph (0, 0)][DBLP]
    PKDD, 2000, pp:652-656 [Conf]
  69. Shusaku Tsumoto
    Discovery of Temporal Knowledge in Medical Time-Series Databases Using Moving Average, Multiscale Matching, and Rule Induction. [Citation Graph (0, 0)][DBLP]
    PKDD, 2001, pp:448-459 [Conf]
  70. Shusaku Tsumoto
    Mining Positive and Negative Knowledge in Clinical Databases Based on Rough Set Model. [Citation Graph (0, 0)][DBLP]
    PKDD, 2001, pp:460-471 [Conf]
  71. Shusaku Tsumoto
    Mining Hierarchical Decision Rules from Clinical Databases Using Rough Sets aaand Medical Diagnostic Model. [Citation Graph (0, 0)][DBLP]
    PKDD, 2002, pp:423-434 [Conf]
  72. Shusaku Tsumoto
    Mining Rules of Multi-level Diagnostic Procedure from Databases. [Citation Graph (0, 0)][DBLP]
    PKDD, 2003, pp:459-470 [Conf]
  73. Shusaku Tsumoto
    Extraction of Experts' Decision Process from Clinical Databases Using Rough Set Model. [Citation Graph (0, 0)][DBLP]
    PKDD, 1997, pp:58-67 [Conf]
  74. Shusaku Tsumoto
    Discovery of Approximate Medical Knowledge Based on Rough Set Model. [Citation Graph (0, 0)][DBLP]
    PKDD, 1998, pp:468-476 [Conf]
  75. Shusaku Tsumoto
    Rule Discovery in Large Time-Series Medical Databases. [Citation Graph (0, 0)][DBLP]
    PKDD, 1999, pp:23-31 [Conf]
  76. Shusaku Tsumoto
    Knowledge Discovery in Medical Multi-databases: A Rough Set Approach. [Citation Graph (0, 0)][DBLP]
    PKDD, 1999, pp:147-155 [Conf]
  77. Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
    Evaluating Learning Models for a Rule Evaluation Support Method Based on Objective Indices. [Citation Graph (0, 0)][DBLP]
    RSCTC, 2006, pp:687-695 [Conf]
  78. Shoji Hirano, Shusaku Tsumoto
    Segmentation of Medical Images Based on Approximations in Rough Set Theory. [Citation Graph (0, 0)][DBLP]
    Rough Sets and Current Trends in Computing, 2002, pp:554-563 [Conf]
  79. Shoji Hirano, Shusaku Tsumoto
    On the Degree of Independence of a Contingency Matrix. [Citation Graph (0, 0)][DBLP]
    Rough Sets and Current Trends in Computing, 2004, pp:219-228 [Conf]
  80. Shoji Hirano, Shusaku Tsumoto
    Detection of Differences between Syntactic and Semantic Similarities. [Citation Graph (0, 0)][DBLP]
    Rough Sets and Current Trends in Computing, 2004, pp:529-538 [Conf]
  81. Shoji Hirano, Shusaku Tsumoto
    A Framework for Unsupervised Selection of Indiscernibility Threshold in Rough Clustering. [Citation Graph (0, 0)][DBLP]
    RSCTC, 2006, pp:872-881 [Conf]
  82. Shusaku Tsumoto
    An Approach to Statistical Extention of Rough Set Rule Induction. [Citation Graph (0, 0)][DBLP]
    Rough Sets and Current Trends in Computing, 2000, pp:362-369 [Conf]
  83. Shusaku Tsumoto
    Diagnostic Reasoning from the Viewpoint of Rough Sets. [Citation Graph (0, 0)][DBLP]
    Rough Sets and Current Trends in Computing, 2000, pp:495-502 [Conf]
  84. Shusaku Tsumoto
    Accuracy and Coverage in Rough Set Rule Induction. [Citation Graph (0, 0)][DBLP]
    Rough Sets and Current Trends in Computing, 2002, pp:373-380 [Conf]
  85. Shusaku Tsumoto
    Statistical Test for Rough Set Approximation Based on Fisher's Exact Test. [Citation Graph (0, 0)][DBLP]
    Rough Sets and Current Trends in Computing, 2002, pp:381-388 [Conf]
  86. Shusaku Tsumoto
    Pawlak Rough Set Model, Medical Reasoning and Rule Mining. [Citation Graph (0, 0)][DBLP]
    RSCTC, 2006, pp:53-70 [Conf]
  87. Shusaku Tsumoto
    Modelling Medical Diagnostic Rules Based on Rough Sets. [Citation Graph (0, 0)][DBLP]
    Rough Sets and Current Trends in Computing, 1998, pp:475-482 [Conf]
  88. Shusaku Tsumoto, Shoji Hirano
    Distribution of Determinants of Contingency Matrix. [Citation Graph (0, 0)][DBLP]
    RSCTC, 2006, pp:567-576 [Conf]
  89. Shusaku Tsumoto, Shoji Hirano
    Interpretation of Contingency Matrix Using Marginal Distributions. [Citation Graph (0, 0)][DBLP]
    RSCTC, 2006, pp:577-586 [Conf]
  90. Shusaku Tsumoto, Kimiko Matsuoka, Shigeki Yokoyama
    Risk Mining: Mining Nurses' Incident Factors and Application of Mining Results to Prevention of Incidents. [Citation Graph (0, 0)][DBLP]
    RSCTC, 2006, pp:706-715 [Conf]
  91. Shusaku Tsumoto, Hiroshi Tanaka
    PRIMEROSE: Probabilistic Rule Induction Method Based on Rough Set Theory. [Citation Graph (0, 0)][DBLP]
    RSKD, 1993, pp:274-281 [Conf]
  92. Shusaku Tsumoto, Hiroshi Tanaka
    AQ, Rough Sets, and Matroid Theory. [Citation Graph (0, 0)][DBLP]
    RSKD, 1993, pp:290-297 [Conf]
  93. Shoji Hirano, Shusaku Tsumoto
    A Clustering Method for Spatio-temporal Data and Its Application to Soccer Game Records. [Citation Graph (0, 0)][DBLP]
    RSFDGrC (1), 2005, pp:612-621 [Conf]
  94. Shusaku Tsumoto
    Extracting Structure of Medical Diagnosis: Rough Set Approach. [Citation Graph (0, 0)][DBLP]
    RSFDGrC, 2003, pp:78-88 [Conf]
  95. Shusaku Tsumoto
    Characteristics of Accuracy and Coverage in Rule Induction. [Citation Graph (0, 0)][DBLP]
    RSFDGrC, 2003, pp:237-244 [Conf]
  96. Shusaku Tsumoto
    Linear Independence in Contingency Table. [Citation Graph (0, 0)][DBLP]
    RSFDGrC, 2003, pp:316-319 [Conf]
  97. Shusaku Tsumoto
    Discovery of Rules about Compilations - A Rough Set Approach in Medical Knowledge Discovery. [Citation Graph (0, 0)][DBLP]
    RSFDGrC, 1999, pp:29-37 [Conf]
  98. Shusaku Tsumoto, Shoji Hirano
    On Degree of Dependence Based on Contingency Matrix. [Citation Graph (0, 0)][DBLP]
    RSFDGrC (1), 2005, pp:471-480 [Conf]
  99. Shusaku Tsumoto, Tsau Young Lin
    Context-Free Fuzzy Sets in Data Mining Context. [Citation Graph (0, 0)][DBLP]
    RSFDGrC, 1999, pp:212-220 [Conf]
  100. Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
    Developing a Rule Evaluation Support Method Based on Objective Indices. [Citation Graph (0, 0)][DBLP]
    RSKT, 2006, pp:456-461 [Conf]
  101. Shoji Hirano, Shusaku Tsumoto
    A Parallel, Structural Comparison Scheme of Time-Series Implemented on a PC Cluster. [Citation Graph (0, 0)][DBLP]
    SAINT Workshops, 2005, pp:344-347 [Conf]
  102. Shusaku Tsumoto
    Web based medical decision support system: application of internet to telemedicine. [Citation Graph (0, 0)][DBLP]
    SAINT Workshops, 2003, pp:288-293 [Conf]
  103. Shusaku Tsumoto
    Web Based Medical Decision Support System for Neurological Diseases. [Citation Graph (0, 0)][DBLP]
    Web Intelligence, 2003, pp:629-632 [Conf]
  104. Shusaku Tsumoto, Shoji Hirano, Hidenao Abe, Hideaki Nakakuni, Eisuke Hanada
    Clinical Decision Support Based on Mobile Telecommunication Systems. [Citation Graph (0, 0)][DBLP]
    Web Intelligence, 2005, pp:700-703 [Conf]
  105. Shusaku Tsumoto, Hiroshi Tanaka
    Algebraic Formulation of Empirical Learning Methods Based on Rough Sets and Matroid Theory. [Citation Graph (0, 0)][DBLP]
    WOCFAI, 1995, pp:393-404 [Conf]
  106. Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Hideto Yokoi, Takahira Yamaguchi
    Evaluating Learning Algorithms with Meta-learning Schemes for a Rule Evaluation Support Method Based on Objective Indices. [Citation Graph (0, 0)][DBLP]
    PKAW, 2006, pp:75-88 [Conf]
  107. Shusaku Tsumoto, Shoji Hirano
    Linear independence in a contingency table. [Citation Graph (0, 0)][DBLP]
    GrC, 2005, pp:646-651 [Conf]
  108. Shusaku Tsumoto, Shoji Hirano
    Degree of Dependence as Granularity in a Contingency Table. [Citation Graph (0, 0)][DBLP]
    GrC, 2005, pp:63-69 [Conf]
  109. Shoji Hirano, Shusaku Tsumoto
    An indiscernibility-based clustering method. [Citation Graph (0, 0)][DBLP]
    GrC, 2005, pp:468-473 [Conf]
  110. Shusaku Tsumoto, Hiroshi Tanaka
    PRIMEROSE: Probabilistic Rule Induction Method based on Rough Sets and Resampling Methods. [Citation Graph (0, 0)][DBLP]
    Computational Intelligence, 1995, v:11, n:, pp:389-405 [Journal]
  111. Shusaku Tsumoto
    Statistical Independence as Linear Independence. [Citation Graph (0, 0)][DBLP]
    Electr. Notes Theor. Comput. Sci., 2003, v:82, n:4, pp:- [Journal]
  112. Shusaku Tsumoto
    Rough Set Based Automatic Classification of Musical Instrument Sounds. [Citation Graph (0, 0)][DBLP]
    Electr. Notes Theor. Comput. Sci., 2003, v:82, n:4, pp:- [Journal]
  113. Shusaku Tsumoto
    Automated extraction of hierarchical decision rules from clinical databases using rough set model. [Citation Graph (0, 0)][DBLP]
    Expert Syst. Appl., 2003, v:24, n:2, pp:189-197 [Journal]
  114. Shusaku Tsumoto
    Extraction of Structure of Medical Diagnosis from Clinical Data. [Citation Graph (0, 0)][DBLP]
    Fundam. Inform., 2004, v:59, n:2-3, pp:271-285 [Journal]
  115. Shusaku Tsumoto, Hiroshi Tanaka
    A Common Algebraic Framework of Empirical Learning Methods Based on Rough Sets and Matroid Theory. [Citation Graph (0, 0)][DBLP]
    Fundam. Inform., 1996, v:27, n:2/3, pp:273-288 [Journal]
  116. Shusaku Tsumoto
    Extraction of Experts' Decision Rules from Clinical Databases Using Rough Set Model. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 1998, v:2, n:1-4, pp:215-227 [Journal]
  117. Shoji Hirano, Shusaku Tsumoto
    Rough representation of a region of interest in medical images. [Citation Graph (0, 0)][DBLP]
    Int. J. Approx. Reasoning, 2005, v:40, n:1-2, pp:23-34 [Journal]
  118. Shusaku Tsumoto, Hiroshi Tanaka, Hiromi Amano, Kimie Ohyama, Takayuki Kuroda
    COBRA: Integration of Heterogeneous Knowledge-Bases in Medical Domain. [Citation Graph (0, 0)][DBLP]
    Int. J. Cooperative Inf. Syst., 1995, v:4, n:4, pp:387-404 [Journal]
  119. Shusaku Tsumoto, Shoji Hirano
    Automated discovery of chronological patterns in long time-series medical datasets. [Citation Graph (0, 0)][DBLP]
    Int. J. Intell. Syst., 2005, v:20, n:7, pp:737-757 [Journal]
  120. Shoji Hirano, Xiaoguang Sun, Shusaku Tsumoto
    Comparison of clustering methods for clinical databases. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 2004, v:159, n:2, pp:155-165 [Journal]
  121. Shusaku Tsumoto
    Knowledge discovery in clinical databases and evaluation of discovered knowledge in outpatient clinic. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 2000, v:124, n:1-4, pp:125-137 [Journal]
  122. Shusaku Tsumoto
    Mining diagnostic rules from clinical databases using rough sets and medical diagnostic model. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 2004, v:162, n:2, pp:65-80 [Journal]
  123. Shusaku Tsumoto
    Automated Extraction of Medical Expert System Rules from Clinical Databases on Rough Set Theory. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 1998, v:112, n:1-4, pp:67-84 [Journal]
  124. Shusaku Tsumoto, Shoji Hirano, Akira Yasuda, Kouhei Tsumoto
    Analysis of amino-acid sequences by statistical technique. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 2002, v:145, n:3-4, pp:205-214 [Journal]
  125. Shoji Hirano, Shusaku Tsumoto
    An Indiscernibility-Based Clustering Method with Iterative Refinement of Equivalence Relations -Rough Clustering-. [Citation Graph (0, 0)][DBLP]
    JACIII, 2003, v:7, n:2, pp:169-177 [Journal]
  126. Shusaku Tsumoto
    Chance Discovery in Medicine - Detection of Rare Risky Events in Chronic Diseases. [Citation Graph (0, 0)][DBLP]
    New Generation Comput., 2003, v:21, n:2, pp:- [Journal]
  127. Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
    Evaluating a Constructive Meta-learning Algorithm for a Rule Evaluation Support Method Based on Objective Indices. [Citation Graph (0, 0)][DBLP]
    KES (2), 2007, pp:934-941 [Conf]
  128. Shusaku Tsumoto, Shoji Hirano
    Visualization of Similarities and Dissimilarities Between Rules Using Multidimensional Scaling. [Citation Graph (0, 0)][DBLP]
    KES (2), 2007, pp:978-986 [Conf]
  129. Shusaku Tsumoto
    Attribute Generalization and Fuzziness in Data Mining Contexts. [Citation Graph (0, 0)][DBLP]
    RSFDGrC, 2007, pp:379-386 [Conf]
  130. Shusaku Tsumoto
    Medical Reasoning and Rough Sets. [Citation Graph (0, 0)][DBLP]
    RSEISP, 2007, pp:90-100 [Conf]
  131. Shusaku Tsumoto, Shoji Hirano
    Visualization of Differences between Rules' Syntactic and Semantic Similarities using Multidimensional Scaling. [Citation Graph (0, 0)][DBLP]
    Fundam. Inform., 2007, v:78, n:4, pp:561-573 [Journal]

  132. Evaluating Learning Algorithms to Construct Rule Evaluation Models Based on Objective Rule Evaluation Indices. [Citation Graph (, )][DBLP]


  133. Charcteristics of Pearson Residuals in a Contingency Matrix. [Citation Graph (, )][DBLP]


  134. Statistical independence in three-variables contingency cube. [Citation Graph (, )][DBLP]


  135. Qualitative fuzzy sets and granularity. [Citation Graph (, )][DBLP]


  136. Fuzziness from attribute generalization in information table. [Citation Graph (, )][DBLP]


  137. Evaluating a method to detect temporal trends of phrases in research documents. [Citation Graph (, )][DBLP]


  138. Analysis of Research Keys as Tempral Patterns of Technical Term Usages in Bibliographical Data. [Citation Graph (, )][DBLP]


  139. Mining Trajectories of Laboratory Data using Multiscale Matching and Clustering. [Citation Graph (, )][DBLP]


  140. Trajectory Analysis of Laboratory Tests as Medical Complex Data Mining. [Citation Graph (, )][DBLP]


  141. Analysis of Relationship between Blood Stream Infection and Clinical Background in Patients’ Lactobacillus Therapy by Data Mining. [Citation Graph (, )][DBLP]


  142. Identifying Exacerbating Cases in Chronic Diseases Based on the Cluster Analysis of Trajectory Data on Laboratory Examinations. [Citation Graph (, )][DBLP]


  143. Statistical Independence and Contingency Matrix. [Citation Graph (, )][DBLP]


  144. Comparing Accuracies of Rule Evaluation Models to Determine Human Criteria on Evaluated Rule Sets. [Citation Graph (, )][DBLP]


  145. Detecting Similarity of Transferring Datasets Based on Features of Classification Rules. [Citation Graph (, )][DBLP]


  146. Hospital Management Based on Data Mining. [Citation Graph (, )][DBLP]


  147. Analyzing Behavior of Objective Rule Evaluation Indices Based on Pearson Product-Moment Correlation Coefficient. [Citation Graph (, )][DBLP]


  148. Detecting Temporal Trends of Technical Phrases by Using Importance Indices and Linear Regression. [Citation Graph (, )][DBLP]


  149. Data Mining Analysis of Relationship Between Blood Stream Infection and Clinical Background in Patients Undergoing Lactobacillus Therapy. [Citation Graph (, )][DBLP]


  150. International Workshop on Risk Informatics (RI2007). [Citation Graph (, )][DBLP]


  151. Discovery of Risky Cases in Chronic Diseases: An Approach Using Trajectory Grouping. [Citation Graph (, )][DBLP]


  152. Analyzing Behavior of Objective Rule Evaluation Indices Based on a Correlation Coefficient. [Citation Graph (, )][DBLP]


  153. Evaluation of a Classification Rule Mining Algorithm Based on Secondary Differences. [Citation Graph (, )][DBLP]


  154. Detecting Temporal Patterns of Importance Indices about Technical Phrases. [Citation Graph (, )][DBLP]


  155. Detection of Risk Factors as Temporal Data Mining. [Citation Graph (, )][DBLP]


  156. Finding Functional Groups of Objective Rule Evaluation Indices Using PCA. [Citation Graph (, )][DBLP]


  157. Statistical Independence of Multi-variables from the Viewpoint of Linear Algebra. [Citation Graph (, )][DBLP]


  158. Implementing a Rule Generation Method Based on Secondary Differences of Two Criteria. [Citation Graph (, )][DBLP]


  159. Representation of Granularity for Non-Euclidian Relational Data by Jaccard Coefficients and Binary Classifications. [Citation Graph (, )][DBLP]


  160. Comparing Temporal Behavior of Phrases on Multiple Indexes with a Burst Word Detection Method. [Citation Graph (, )][DBLP]


  161. Multiscale Comparison of Three-Dimensional Trajectories: A Preliminary Step. [Citation Graph (, )][DBLP]


  162. Hierarchical Clustering of Non-Euclidean Relational Data Using Indiscernibility-Level. [Citation Graph (, )][DBLP]


  163. Analyzing Correlation Coefficients of Objective Rule Evaluation Indices on Classification Rules. [Citation Graph (, )][DBLP]


  164. A Comparison of Composed Objective Rule Evaluation Indices Using PCA and Single Indices. [Citation Graph (, )][DBLP]


  165. Evaluating learning algorithms for a rule evaluation support method. [Citation Graph (, )][DBLP]


  166. Contingency matrix theory. [Citation Graph (, )][DBLP]


  167. Dealing with granularity on non-euclidean relational data based on indiscernibility level. [Citation Graph (, )][DBLP]


  168. Pearson Residuals in Multi-way Contingency Tables. [Citation Graph (, )][DBLP]


  169. Distribution of Derminants of Contingency Tables. [Citation Graph (, )][DBLP]


  170. Detecting Temporal Patterns of Technical Phrases by using Importance Indices in a Research Documents. [Citation Graph (, )][DBLP]


  171. Mining Diagnostic Taxonomy and Diagnostic Rules for Multi-Stage Medical Diagnosis from Hospital Clinical Data. [Citation Graph (, )][DBLP]


  172. Meaning of Pearson Residuals - Linear Algebra View. [Citation Graph (, )][DBLP]


  173. Evaluation of Learning Costs of Rule Evaluation Models Based on Objective Indices to Predict Human Hypothesis Construction Phases. [Citation Graph (, )][DBLP]


  174. Detection of trends of technical phrases in text mining. [Citation Graph (, )][DBLP]


  175. Multivariate statistical independence and contingency tables. [Citation Graph (, )][DBLP]


  176. Hierarchical Clustering of Asymmetric Proximity Data based on the Indiscernibility-level. [Citation Graph (, )][DBLP]


  177. Decomposition of Pearson Residuals of Three-variables Contingency Cube. [Citation Graph (, )][DBLP]


  178. Investigating Accuracies of Rule Evaluation Models on Randomized Labeling and Human Evaluation. [Citation Graph (, )][DBLP]


  179. Geometrical and Combinatorial Nature of Pearson Residuals. [Citation Graph (, )][DBLP]


  180. Qualitative Simulation Based on Ranked Hyperreals. [Citation Graph (, )][DBLP]


  181. Hierarchical, Granular Representation of Non-metric Proximity Data. [Citation Graph (, )][DBLP]


  182. Information Granules of Statistical Dependence in Multiway Contingency Tables. [Citation Graph (, )][DBLP]


  183. Risk Mining in Medicine: Application of Data Mining to Medical Risk Management. [Citation Graph (, )][DBLP]


  184. Mining Rules for Risk Factors on Blood Stream Infection in Hospital Information System. [Citation Graph (, )][DBLP]


  185. Evaluating Learning Models with Transitions of Human Interests Based on Objective Rule Evaluation Indices. [Citation Graph (, )][DBLP]


  186. Multiscale Comparison of Three-Dimensional Trajectories Based on the Curvature Maxima and Its Application to Medicine. [Citation Graph (, )][DBLP]


  187. Cluster analysis of long time-series medical datasets. [Citation Graph (, )][DBLP]


  188. Rank and independence in contingency table. [Citation Graph (, )][DBLP]


  189. Evaluation of rule interestingness measures in medical knowledge discovery in databases. [Citation Graph (, )][DBLP]


  190. Evaluating Learning Algorithms to Support Human Rule - Evaluation Based on Objective Rule Evaluation Indices. [Citation Graph (, )][DBLP]


Search in 0.072secs, Finished in 0.077secs
NOTICE1
System may not be available sometimes or not working properly, since it is still in development with continuous upgrades
NOTICE2
The rankings that are presented on this page should NOT be considered as formal since the citation info is incomplete in DBLP
 
System created by asidirop@csd.auth.gr [http://users.auth.gr/~asidirop/] © 2002
for Data Engineering Laboratory, Department of Informatics, Aristotle University © 2002