{"id":61,"date":"2022-12-22T09:44:09","date_gmt":"2022-12-22T00:44:09","guid":{"rendered":"https:\/\/www.comm.tcu.ac.jp\/mikawalab\/?page_id=61"},"modified":"2026-04-15T15:06:49","modified_gmt":"2026-04-15T06:06:49","slug":"%e5%9b%bd%e9%9a%9b%e4%bc%9a%e8%ad%b0%e7%99%ba%e8%a1%a8","status":"publish","type":"page","link":"https:\/\/www.comm.tcu.ac.jp\/mikawalab\/%e7%a0%94%e7%a9%b6%e6%a5%ad%e7%b8%be\/%e5%9b%bd%e9%9a%9b%e4%bc%9a%e8%ad%b0%e7%99%ba%e8%a1%a8","title":{"rendered":"\u56fd\u969b\u4f1a\u8b70"},"content":{"rendered":"\r\n

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  1. K. Mikawa, M. Kobayashi, T. Sasaki, and A. Manada, \"A Multi-Domain Relational Data Analysis Model with Varying Latent Dimensions, \" 2026 2nd International Conference on Consumer Technology (ICCT-Pacific)<\/em>, pp. 172-175, 2026-3.<\/li>\r\n
  2. T.Fukuda, and K. Mikawa, \"Extending the Semi-supervised Signed Stochastic Block Model to Multiple Domains, \" Asian Conference of Management Science & Applications (ACMSA2025), 2025.12.<\/li>\r\n
  3. Y. Sakai, K. Mikawa, M. Goto: \"A Study on Attribute Similarity Interpretation Method Based on Customer Behavior Using the ECOC Approach,\" The 8th Asian Conference of Management Science and Applications (ACMSA2025), Shanghai, China, ID:61, 2025-12.<\/li>\r\n
  4. Y. Sakai, K. Mikawa, M. Goto: \"Proposal of an Explainable Multiclass Classification Method Using Neural Networks with ECOC Approach,\" The 52nd International Conference on Computers and Industrial Engineering (CIE52), INSA Lyon, France, CIE2025-125, 2025-11.<\/li>\r\n
  5. K. Mikawa, M. Kobayashi, T. Sasaki, and A. Manada, \"Latent Structure Analysis for Relational Data with Attribute Information to Multiple Domains,\" Proc. 2025 International Symposium on Nonlinear Theory and Its Applications, pp. 618 -- 621, 2025-10.<\/li>\r\n
  6. K. Mikawa, M. Kobayashi, T. Sasaki, and A. Manada, \"Integrating Attribute Information into Relational Data: A Latent Structure Approach, \" 2025 1st International Conference on Consumer Technology (ICCT-Pacific)<\/em>, pp. 1-4, 2025-3.<\/li>\r\n
  7. Y. Sakai, K. Mikawa, and M. Goto, \"High-dimensional\u00a0Supervised\u00a0Embedding\u00a0and\u00a0Visualization\u00a0Method\u00a0using\u00a0von\u00a0Mises\u00a0Distribution, \" The 22nd Asian Network for Quality Congress (ANQ Congress 2024), 2024-9.<\/li>\r\n\r\n\r\n\r\n
  8. K. Mikawa, M. Kobayashi, T. Sasaki, and A. Manada, \"A Study on Latent Structural Models for Binary Relational Data with Attribute Information,\"
    Proc. 2023 International Symposium on Nonlinear Theory and Its Applications, 2023-9.<\/li>\r\n\r\n\r\n\r\n
  9. K. Mikawa, M. Kobayashi, M. Goto, and S. Hirasawa, \"Learning and Estimation of Latent Structural Models Based on between-Data Metrics,\" Proc. 2022 IEEE International Conference on Systems, Man, and Cybernetics(SMC), 2022-10.<\/li>\r\n\r\n\r\n\r\n
  10. K. Mikawa \"Factorization Machine with Mixed Norm Regularization using ADMM,\" Proc. 20th Asia Pacific Industrial Engineering and Management System (APIEMS2019), 2019-12.<\/li>\r\n\r\n\r\n\r\n
  11. S. Nakano, K. Mikawa, and M. Goto, \u201cA Study of the Application of Canonical Correlation Forests to Text Classification,\u201d The 19th Asia Pacific Industrial Engineering and Management Systems (APIEMS 2018), 2018-12.<\/li>\r\n\r\n\r\n\r\n
  12. K. Mikawa, M. Kobayashi, M. Goto and S. Hirasawa, \u201cProposal for an l1 regularized Factorization Machine,\u201d The 19th Asia Pacific Industrial Engineering and Management Systems (APIEMS 2018), 2018-12.<\/li>\r\n\r\n\r\n\r\n
  13. T. Sugisaki, Y. Nishio, K. Mikawa, M. Goto, and T. Sakurai, \u201cA New Entry Behavior Model of Student Users on Job Board for New Graduates Considering the Interaction between Features,\u201d 16th Asian Network for Quality Congress,\u00a02018-9.<\/li>\r\n\r\n\r\n\r\n
  14. M. Kobayashi, K. Mikawa, M. Goto, T. Matsushima, and S. Hirasawa, \"Collaborative Filtering Based on the Latent Class Model for Attributes\", 16th IEEE International Conference on Machine Learning and Applications (ICMLA), 2017-12.<\/li>\r\n\r\n\r\n\r\n
  15. K. Mikawa, M. Kobayashi, M. Goto and S. Hirasawa, \"Distance metric learning using each category centroid with nuclear norm regularization,\" 2017 Symposium Series on Computational Intelligence (SSCI), 2017-12.<\/li>\r\n\r\n\r\n\r\n
  16. S. Okayama, H. Yamashita, K. Mikawa, M. Goto, and T. Yoshikai, \"Relational Analysis Model of Weather Conditions and Sales Patterns Based on Nonnegative Matrix Factorization,\" The 18th Asia Pacific Industrial Engineering and Management System Conference(APIEMS 2017),\u00a02017-12.<\/li>\r\n\r\n\r\n\r\n
  17. T. Arai, K. Mikawa, and M. Goto, \"The Bayesian Prediction Algorithm Using Logistic Regression,\" The 18th Asia Pacific Industrial Engineering and Management System Conference(APIEMS 2017),\u00a02017-12.<\/li>\r\n\r\n\r\n\r\n
  18. M. Suzuki, N. Yamagishi, K. Mikawa, and M. Goto, \"Characteristics of a Word Segmentation Method Based on a State-transition Model,\" The 18th Asia Pacific Industrial Engineering and Management System Conference(APIEMS 2017),\u00a02017-12.<\/li>\r\n\r\n\r\n\r\n
  19. M. Ninohira, K. Mikawa, and M. Goto \"A Study on Prediction Model of Selling Prices of Second-hand Fashion Items,\" The 18th Asia Pacific Industrial Engineering and Management System Conference(APIEMS 2017),\u00a02017-12.<\/li>\r\n\r\n\r\n\r\n
  20. S. Nakano, K. Mikawa, and M. Goto, \"A Study on Analytical Method of Printer Data Log for Detecting Excellent Customers,\"
    2017 Asian Conference of Management Science & Applications\u00a02017-12.<\/li>\r\n\r\n\r\n\r\n
  21. K. Mikawa, M. Kobayashi, M. Goto, and S. Hirasawa, \"Distance Metric Learnig using Each Category Centroid with Nuclear Norm Regularization\", The 2017 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2017), 2017-11.<\/li>\r\n\r\n\r\n\r\n
  22. M. Kobayashi, K. Mikawa, M. Goto, and S. Hirasawa, \"Collaborative Filtering Analysis of Consumption Behavior Based on the Latent Class Model\", 2017 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC2017), 2017-10.<\/li>\r\n\r\n\r\n\r\n
  23. M. Goto, K. Mikawa, M. Kobayashi, and S. Hirasawa, \"A Bayes prediction algorithm for model class composed of several subclasses,\" 2016 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC2016), 2016-10.<\/li>\r\n\r\n\r\n\r\n
  24. K. Mikawa, M. Kobayashi, M. Goto, and S. Hirasawa, \"Distance metric learning based on different \u21131 regularized metric matrices in each category,\" 2016 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC2016), 2016-10.<\/li>\r\n\r\n\r\n\r\n
  25. Y. Matsuzaki, K. Yamagami, K. Mikawa and M. Goto, \u201cAnalysis of customer purchase behavior by using purchase history with discount coupon based on latent class model,\" 16th Asia Pacific Industrial Engineering and Management Society (16th APIEMS), 2015-12.<\/li>\r\n\r\n\r\n\r\n
  26. L. Suzuki, K. Yamagami, K. Mikawa, and M. Goto, \u201cMulti-valued Classification of Text Data based on ECOC Approach using Ternary Orthogonal Table,\" 16th Asia Pacific Industrial Engineering and Management Society (16th APIEMS), 2015-12.<\/li>\r\n\r\n\r\n\r\n
  27. S. Misawa, K. Mikawa, and M. Goto, \u201cAdaptive Prediction Method Based on Alternating Decision Forests considering Generalization Ability,\" 16th Asia Pacific Industrial Engineering and Management Society (16th APIEMS), 2015-12.<\/li>\r\n\r\n\r\n\r\n
  28. K. Yamagami, K. Mikawa, M. Goto and T. Ogihara, \u201cA Statistical Prediction Model of Students \u2019 Success Date on Job Hunting Using Internet Portal Sites Data,\" 16th Asia Pacific Industrial Engineering and Management Society (16th APIEMS), 2015-12.<\/li>\r\n\r\n\r\n\r\n
  29. S. Nagamori, K. Yamagami, K. Mikawa, M. Goto and T. Ogihara, \u201cA Finish Date Prediction of Job Hunting based on User Clustering Approach considering Time Series Variation of Entry Tendencies,\" 16th Asia Pacific Industrial Engineering and Management Society (16th APIEMS), 2015-12.<\/li>\r\n\r\n\r\n\r\n
  30. Y. Yamamoto, K. Mikawa and M. Goto, \u201cA Proposal for the Classification Method of Documents Data with Unobserved Categories Considering Latent Topics,\" 16th Asia Pacific Industrial Engineering and Management Society (16th APIEMS), 2015-12.<\/li>\r\n\r\n\r\n\r\n
  31. K. Mikawa, M. Kobayashi, M. Goto, and H. Hirasawa, \u201cA Study of Distance Metric Learning by Considering the Distances between Category Centroids,\" 2015 IEEE International Conference on Systems, Man, and Cybernetics (SMC2015), pp.1645-1650, 2015-10.<\/li>\r\n\r\n\r\n\r\n
  32. K. Yukawa, K. Mikawa, M. Goto,\u00a0\u201cThe Study of Distributed Support Vector Machine with Lower Time Computational Complexity,\u201d\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Asian Conference of Management Science & Applications (ACMSA2015), No. 47, 2015-9.<\/li>\r\n\r\n\r\n\r\n
  33. T. Maga, K. Yukawa, K. Mikawa, M. Goto, \"Data pair selection for improving classification accuracy of Information-Theoretic Metric Learning,\" Asian Conference of Management Science & Applications (ACMSA2015), No. 22, 2015.9.<\/li>\r\n\r\n\r\n\r\n
  34. Q. Zhang, H, Yamashita, K. Mikawa, M. Goto \u201cAnalysis of Purchase History Data Based on a New Latent Class for RFM Analysis,\u201d Asian Conference of Management Science & Applications (ACMSA2015), No. 39, 2015.9.<\/li>\r\n\r\n\r\n\r\n
  35. H. Auchi, K. Mikawa, M. Goto \u201cA Bayes Prediction Algorithm for the Model Class Conditioned by the Cumulative Number of Event Occurrences,\" Asian Conference of Management Science & Applications (ACMSA2015), 2015.9.<\/li>\r\n\r\n\r\n\r\n
  36. H. Saito, K. Mikawa, M. Goto \u201cA Proposal of Classification Method Based on Local Metric Matrices,\u201d\u00a0 Asian Conference of Management Science & Applications (ACMSA2015), 2015.9.<\/li>\r\n\r\n\r\n\r\n
  37. M. Goto, K. Mikawa, M. Kobayashi, S. Horii, T. Suko, and S. Hirasawa, \u201cAn Analysis of Purchasing and Browsing Histories on an EC Site Based on a New Latent Class Model,\" The 1st East Asia Workshop on Industrial Engineering, 2014-11.<\/li>\r\n\r\n\r\n\r\n
  38. S. Misawa, N. Fujiwara, K. Mikawa, and M. Goto, \u201cA Prediction Method based on Weighted Ensemble of Decision Trees on Alternating Decision Forests,\" 15th Asia Pacific Industrial Engineering and Management Society (15th APIEMS), 2014-10.<\/li>\r\n\r\n\r\n\r\n
  39. N. Fujiwara, K. Mikawa, and M. Goto, \u201cA New Estimation Method of Latent Class Model with High Accuracy by Using Both Browsing and Purchase Histories,\" 15th Asia Pacific Industrial Engineering and Management Society (15th APIEMS), 2014-10.<\/li>\r\n\r\n\r\n\r\n
  40. K. Yamagami, N. Fujiwara, K. Mikawa, and M. Goto, \u201cA Statistical Model for Recommender System to Maximize Sales Amount Focusing on Characteristics of EC Site Data,\" 15th Asia Pacific Industrial Engineering and Management Society (15th APIEMS), 2014-10.<\/li>\r\n\r\n\r\n\r\n
  41. H. Saito, F. Yamazaki, K. Mikawa, and M. Goto, \u201cDistance Metric Learning with Low Computational Complexity based on Ensemble of the Low-dimensional Matrixes,\" 15th Asia Pacific Industrial Engineering and Management Society (15th APIEMS), 2014-10.<\/li>\r\n\r\n\r\n\r\n
  42. K. Yukawa, K. Mikawa, and M. Goto, \u201cStatistical Model Selection of Liner Regression for Privacy Preserving Data Mining,\" 15th Asia Pacific Industrial Engineering and Management Society (15th APIEMS), 2014-10.<\/li>\r\n\r\n\r\n\r\n
  43. M. Goto, K. Minetoma, K. Mikawa, M. Kobayashi, and S. Hirasawa, \u201cA Modified Aspect Model for Simulation Analysis,\" IEEE International Conference on Systems, Mans and Cybanetics (SMC2014), pp.1306-1311, 2014-10.<\/li>\r\n\r\n\r\n\r\n
  44. K. Mikawa, M. Kobayashi, M. Goto, and H. Hirasawa, \u201cA Proposal of l1 Regularized Distance Metric Learning for High Dimensional Sparse Vector Space,\" 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC2014), pp.1741-1746, 2014-10.<\/li>\r\n\r\n\r\n\r\n
  45. Y. Matsuzaki, S, Nagamori, K. Mikawa, M. Goto, and B. Bushell, \u201cA Comparative Survey on Sustainable Tourism Development Considering Regional Characteristics in Nepal,\" The conference of the 20th IICE, 2014-6.<\/li>\r\n\r\n\r\n\r\n
  46. K. Mikawa, T. Ishida, and M. Goto, \u201cRegularized Distance Metric Learning and its Application to Knowledge Discovery,\" 14th Asia Paci
    fic Industrial Engineering and Management Society (14th APIEMS), 2013-12.<\/li>\r\n\r\n\r\n\r\n
  47. M. Hayakawa, K. Mikawa, T. Ishida, and M. Goto, \u201cStatistical Prediction Model of Students' Success on Job Hunting by Log Data Analysis,\" 14th Asia Pacific Industrial Engineering and Management Society (14th APIEMS), 2013-12.<\/li>\r\n\r\n\r\n\r\n
  48. S. Sakamoto, K. Mikawa, and M. Goto, \u201cA Study on Recommender System Based on Latent Class Model for High Dimensional and Sparse Data,\" 14th Asia Pacific Industrial Engineering and Management Society (14th APIEMS), 2013-12.<\/li>\r\n\r\n\r\n\r\n
  49. F. Yamazaki, S. Sakamoto, K. Mikawa, and M. Goto \u201cTraining Data Selection in Large Margin Nearest Neighbor Method for Classifi
    cation Problems,\" 14th Asia Pacific Industrial Engineering and Management Society (14th APIEMS), 2013-12.<\/li>\r\n\r\n\r\n\r\n
  50. T. Ogihara, K. Mikawa, and M. Goto \u201cMulti-valued Classification of Text Data based on ECOC Approach considering Parallel Processing,\" 14th Asia Pacific Industrial Engineering and Management Society (14th APIEMS), 2013-12.<\/li>\r\n\r\n\r\n\r\n
  51. T. Oi, K. Mikawa, and M. Goto, \u201cA Study of Recommender Systems Based on the Latent Class Model Estimated by Combining Both Evaluation and Purchase Histories,\" 14th Asia Pacific Industrial Engineering and Management Society (14th APIEMS), 2013-12.<\/li>\r\n\r\n\r\n\r\n
  52. K. Mikawa, T. Ishida, M. Goto, and S. Hirasawa, \u201cA Proposal of Adaptive Metric Learning to Each Category Characteristics for Text Classification,\" 2013 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, pp.544-547, 2013-3<\/li>\r\n\r\n\r\n\r\n
  53. K. Mikawa, T. Ishida, M. Goto, and S. Hirasawa, \u201cAn Optimal Weighting Method by Using the Category Information in Text Classi
    fication based on Metric Learning,\" 13th Asia Pacific Industrial Engineering and Management Society (13th<\/sup> APIEMS), 2012-12. \u3000<\/li>\r\n\r\n\r\n\r\n
  54. Y. Izawa, K. Mikawa, and M. Goto, \u201cThe Agent-Based Simulation Analysis of Collaborative Filtering Using Mixed Membership Stochastic Block Models,\" 13th Asia Pacific Industrial Engineering and Management Society (13th APIEMS), 2012-12.<\/li>\r\n\r\n\r\n\r\n
  55. T. Oi, T. Arakawa, K. Mikawa, and M. Goto, \u201cA Proposal of Improved Na\u00efve Bayes Method for Collaborative Filtering by Introducing Clustering,\" 13th Asia Pacific Industrial Engineering and Management Society (13th APIEMS), 2012-12.<\/li>\r\n\r\n\r\n\r\n
  56. T. Ogihara, K. Mikawa, G. Hosoya, and M. Goto, \u201cMulti-valued Document Classification based on Generalized Bradley-Terry Classifi
    ers Utilizing Accuracy Information,\" 13th Asia Pacific Industrial Engineering and Management Society (13th APIEMS), 2012-12.<\/li>\r\n\r\n\r\n\r\n
  57. S. Sakamoto, Y. Izawa, K. Mikawa, and M. Goto, \u201cA Study for Recommender System based on Mixed and Constrained Latent Dirichlet Allocation,\" 13th Asia Pacific Industrial Engineering and Management Society (13th APIEMS), 2012-12.<\/li>\r\n\r\n\r\n\r\n
  58. T. Suzuki, K. Mikawa, and M. Goto, \u201cA Study of Recommender System to Improve Aggregate Diversity based on Latent Class Model,\" 13th Asia Pacific Industrial Engineering and Management Society (13th APIEMS), 2012-12.<\/li>\r\n\r\n\r\n\r\n
  59. K. Mikawa, G. Kumoi, K. Suzuki, and M. Goto \u201cA Proposal of Extracting Unknown Information from Customer Review for SWOT Analysis,\" 2011 Asian Conference of Management Science & Applications, ID-167, 2011-10.<\/li>\r\n\r\n\r\n\r\n
  60. Y. Izawa, H. Sakaeda, K. Mikawa, and M. Goto, \u201cA Recommender System Considering with Item Evaluation based on Mixed Membership Stochastic Block Models,\" 12th Asia Pacic Industrial Engineering and Management Society (12th APIEMS), ID-118, 2011-10.<\/li>\r\n\r\n\r\n\r\n
  61. T. Suzuki, G. Kumoi, K. Mikawa, and M. Goto, \u201cA study on the recommender system based on probabilistic latent model,\" 12th Asia Pacific Industrial Engineering and Management Society (12th APIEMS), ID-127, 2011-10.<\/li>\r\n\r\n\r\n\r\n
  62. K. Mikawa, T. Ishida, and M. Goto, \u201cAn Optimal Weighting Method in Supervised Learning of Linguistic Model for Text Classifi
    cation,\" 12th Asia Pacific Industrial Engineering and Management Society (12th APIEMS), ID-141, 2011-10.<\/li>\r\n\r\n\r\n\r\n
  63. K. Hibi, G. Kumoi, K. Mikawa, and M. Goto, \u201cAutomated source code plagiarism detection based on coding style model probability based on Relevance Vector Machine,\" 12th Asia Pacific Industrial Engineering and Management Society (12th APIEMS), ID-147, (2011-10)<\/li>\r\n\r\n\r\n\r\n
  64. R. Odai, G. Kumoi, K. Mikawa, G. Hosoya, and M. Goto, \u201cMultivalued document classification by maximization of posterior probability based on Relevance Vector Machine,\" 12th Asia Pacific Industrial Engineering and Management Society (12th \u00a0APIEMS), ID-205, 2011-10.<\/li>\r\n\r\n\r\n\r\n
  65. K. Mikawa, T. Ishida, and M. Goto, \u201cA Proposal of Extended Cosine Measure for Distance Metric Learning in Text Classification,\" 2011 IEEE International Conference on Systems, Man, and Cybernetics (SMC2011), pp.1741-1746, 2011-10.<\/li>\r\n\r\n\r\n\r\n
  66. K. Suzuki, R. Horiuchi, Y. Kurishima, and K. Mikawa, \u201cA Participatory Process toward a Model for Environmental Sustainability,\" Salt of the earth Conference,2006-10<\/li>\r\n\r\n\r\n\r\n
  67. B. Bushell, Y. Kurishima, K. Mikawa, and M. Goto, \u201cCreating Learning Environments through eco-design,\" North American Association for Environmental Education, 34th Annual Conference, 2005-10.<\/li>\r\n<\/ol>\r\n","protected":false},"excerpt":{"rendered":"

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