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MASAHIRO KIMURA, Ph. D.

Professor
Department of Electronics and Informatics
Faculty of Science and Technology
Ryukoku University

Email: kimura@rins.ryukoku.ac.jp
Tel: +81 77 543 7406
Fax: +81 77 543 7428
Address: Department of Electronics and Informatics, Ryukoku University, Seta, Otsu 520-2194, Japan

Recent Papers

  • Minoru Higuchi, Kanji Matsutani, Masahito Kumano, and Masahiro Kimura: Discovering spatio-temporal latent influence in geographical attention dynamics, In M. Berlingerio et al. (Eds.): Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2018), LNAI 11052, pp.517-534, Springer, 2019.

  • Keiko Ono, Yoshiko Hanada, Masahito Kumano, and Masahiro Kimura: Enhancing island model genetic programming by controlling frequent trees, Journal of Artificial Intelligence and Soft Computing Research, Vol.9, No.1, pp.51-65, 2019.

  • Kouzou Ohara, Kazumi Saito, Masahiro Kimura, and Hiroshi Motoda: Critical node identification based on articulation point detection for network with uncertain connectivity, Proceedings of the 6th International Symposium on Computing and Networking (CANDAR'18), pp.146-152, IEEE, 2018.

  • Kazumi Saito, Kouzou Ohara, Masahiro Kimura, and Hiroshi Motoda: Critical link identification based on bridge detection for network with uncertain connectivity, Proceedings of the 24th International Symposium on Methodologies for Intelligent Systems (ISMIS 2018), LNAI 11177, pp.88-99, Springer, 2018.

  • Kazumi Saito, Kouzou Ohara, Masahiro Kimura, and Hiroshi Motoda: Accurate and efficient detection of critical links in network to minimize information loss, Journal of Intelligent Information Systems, Vol.51, No.2, pp.235-255, 2018.

  • Kazumi Saito, Kouzou Ohara, Masahiro Kimura, and Hiroshi Motoda: Efficient detection of critical links to maintain performance of network with uncertain connectivity, Proceedings of the 15th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2018), LNAI 11012, pp.282-295, Springer, 2018.

  • Yuuki Kikuchi, Masahito Kumano, and Masahiro Kimura: Extracting active co-occurrence patterns of cooking ingredient usage in recipe sharing sites, IPSJ Transactions on Mathematical Modeling and its Applications, Vol.11, No.2, pp.30-40, 2018, in Japanese.

  • Kanji Matsutani, Masahito Kumano, Masahiro Kimura, Kazumi Saito, Kouzou Ohara, and Hiroshi Motoda: Extracting cooperative structure among online items from share-event sequence, Transactions of the Japanese Society for Artificial Intelligence, Vol.33, No.3, p.A-HA1_1-12, 2018, in Japanese.

  • Masahito Kumano, Kazuya Hashimoto, and Masahiro Kimura: Digest visualization of photo spots in terms of seasonal uniqueness, Journal of the Society for Art and Science, Vol.17, No.1, pp.8-25, 2018, in Japanese.

  • Kazumi Saito, Kouzou Ohara, Masahiro Kimura, and Hiroshi Motoda: Which is more influential, "who" or "when" for a user to rate in online review site?, Intelligent Data Analysis, Vol.22, No.3, pp.639-657, 2018.

  • Kanji Matsutani, Masahito Kumano, Masahiro Kimura, Kazumi Saito, Kouzou Ohara, and Hiroshi Motoda: Discovering cooperative structure among online items for attention dynamics, Proceedings of 2017 IEEE International Conference on Data Mining Workshops (ICDMW 2017), pp.1033-1041, IEEE, 2017.

  • Yuuki Kikuchi, Masahito Kumano, and Masahiro Kimura: Analyzing dynamical activities of co-occurrence patterns for cooking ingredients, Proceedings of 2017 IEEE International Conference on Data Mining Workshops (ICDMW 2017), pp.17-24, IEEE, 2017.

  • Kouzou Ohara, Kazumi Saito, Masahiro Kimura, and Hiroshi Motoda: Maximizing network performance based on group centrality by creating most effective k-links, Proceedings of the 4th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2017), pp.561-570, IEEE, 2017.

  • Kanji Matsutani and Masahiro Kimura: Learning attention dynamics for items in social media, IPSJ Transactions on Mathematical Modeling and its Applications, Vol.10, No.2, pp.14-24, 2017, in Japanese

  • Hiroki Takahashi and Masahiro Kimura: Analyzing time-decay effects of mediating-objects in creating trust-links, In A. Appice et al. (Eds.), New Frontiers in Mining Complex Patterns, 5th International Workshop, NFMCP 2016, Held in Conjunction with ECML-PKDD 2016, Revised Selected Papers, Lecture Notes in Artificial Intelligence, Vol.10312, pp.99-114, Springer, 2017.

  • Kazumi Saito, Kouzou Ohara, Masahiro Kimura, and Hiroshi Motoda: An accurate and efficient method to detect critical links to maintain information flow in network, Proceedings of the 23rd International Symposium on Methodologies for Intelligent Systems (ISMIS 2017), LNAI 10352, pp.116-126, Springer, 2017.

  • Kouzou Ohara, Kazumi Saito, Masahiro Kimura, and Hiroshi Motoda: Accelerating computation of distance based centrality measures for spatial networks, Proceedings of the 19th International Conference on Discovery Science (DS 2016), LNAI 9956, pp.376-391, Springer, 2016.

  • Kazumi Saito, Masahiro Kimura, Kouzou Ohara, and Hiroshi Motoda: Detecting critical links in complex network to maintain information flow/reachability, Proceedings of the 14th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2016), LNAI 9810, pp.419-432, Springer, 2016.

  • Masahiro Kimura, Kazumi Saito, Kouzou Ohara, and Hiroshi Motoda: Speeding-up node influence computation for huge social networks, International Journal of Data Science and Analytics, Vol.1, pp.3-16, 2016.

  • Kazumi Saito, Masahiro Kimura, Kouzou Ohara, and Hiroshi Motoda: Super mediator - A new centrality measure of node importance for information diffusion over social network, Information Sciences, Vol.329, pp.985-1000, 2016.

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    Last modified on: January 28, 2019.