Akihiro Inokuchi

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@Publications

 

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Journal

1.      Fast and Complete Mining Method for Frequent Graph Patterns, A. Inokuchi, T. Washio, H. Motoda, K. Kumazawa, Arai, Journal of the Japanese Society for Artificial IntelligenceC Vol.15, No. 6, pp.1052-1063 (2000)

2.      Applying the Apriori-based Graph Mining Method to Mutagenesis Data Analysis, A. Inokuchi, T. Washio, T. Okada and H. Motoda, Journal of Computer Aided Chemistry, Vol.2, pp.87-92 (2001) (2002 JCAC Best Paper Award)

3.      Complete Mining of Frequent Patterns from Graphs, A. Inokuchi, T. Washio and H. Motoda, Machine Learning, 50 (3): pp.321-354 (2003)

4.      Fast Apriori-based Graph Mining Algorithm and application to 3-dimensional Structure Analysis, Y. Nishimura , T. Washio, T. Yoshida, H. Motoda, T. Okada, Transaction of the Japanese Society for Artificial Intelligence, Vol. 18, No. 5, pp.257-268 (2003)

5.      Unstructured Information Management Projects at IBM Tokyo Research Laboratory, K. Takeda, H. Watanabe, N. Uramoto, H. Nomiyama, H. Matsuzawa, T. Nasukawa, T. Nagano, A. Murakami, H. Takeuchi, H. Kanayama, M. Kobayashi, M. Aono, A. Inokuchi, M. Houle, Korea Information Processing Society Review, Vol. 11, No. 2, pp. 4-16, (2004).

6.      Text analytics for life science using the Unstructured Information Management Architecture, R. Mack, S. Mukherjea, A. Soffer, N. Uramoto, E. Brown, A. Coden, J. Cooper, A. Inokuchi, B. Iyer, Y. Mass, H. Matsuzawa, L. Subramaniam, IBM Systems Journal, 43(3): pp. 490-515, (2004).

7.      Generalization for Frequent Subgraph Mining, A. Inokuchi, T. Washio, H. Motoda, Transaction of the Japanese Society for Artificial Intelligence, Vol. 19, No. 5, pp.368-378 (2004)

8.      A General Framework for Mining Frequent Subgraphs from Labeled Graphs, A. Inokuchi, T. Washio, and H. Motoda, Fundamenta Informaticae, Vol.66, No.1-2: pp.53-82 (2005)

9.      Interactive Knowledge Discovery for Clinical Decision Intelligence, A. Inokuchi, K. Takeda, N. Inaoka, and F. Wakao, IBM Systems Journal, Vol. 46, No. 1, (2007)

10.    An OLAP System for Text Analysis, A. Inokuchi, K. Takeda, Transaction of database, Information Processing Society of Japan, Vol.48, No. SIG 11 (TOD34), (2007)


International Conference Papers

*: workshop papers

1.      Basket Analysis for Graph Structured Data, A. Inokuchi, T. Washio and H. Motoda, Proc. of the 3rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 1999), pp.420-431, (1999)

2.      Derivation of the Topology Structure from the Massive Graph Data, A. Inokuchi, T. Washio and Motoda, Proc. of the 2nd International Conference on Discovery Science (DS 1999), pp.330-332, (1999)

3.      * Applying Algebraic Mining Method of Graph Substructures to Mutagenesis Data Analysis, A. Inokuchi, T. Washio, T. Okada, H. Motoda, Working notes of International Workshop of KDD Challenge on Real-world Data, KDD Challenge 2000, The 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining pp.41-46, 2000.

4.      An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data, A. Inokuchi, T. Washio and H. Motoda, Proc. of 4th European Conference (PKDD 2000), pp.13-23, 2000

5.      * General Framework for Mining Frequent Patterns in Structure, A. Inokuchi, T. Washio, Yoshio Nishimura and H. Motoda, Working notes of International Workshop on Active Mining: The 2002 IEEE International Conference on Data Mining (ICDM 2002) pp.23-30, 2002.

6.      * Kernels for graph classification, Hisashi Kashima, A. Inokuchi, Working notes of International Workshop on Active Mining: The 2002 IEEE International Conference on Data Mining (ICDM 2002), pp. 31-36. 2002.

7.      Marginalized Kernels between Labeled Graphs, H. Kashima, K. Tsuda, and A. Inokuchi, Proc. of the Twentieth International Conference on Machine Learning (ICML 2003), pp. 321-328, 2003.

8.      * Specific Biases for Mining Frequent Substructure, A. Inokuchi, T. Washio and H. Motoda, Proc. of 1st International Workshop on Mining Graphs, Trees and Sequences (MGTS-2003): ECML/PKDD-2003 pp.45-54 2003.

9.      Mining Significant Pairs of Patterns from Graph Structures with Class Labels, A. Inokuchi and H. Kashima, Proc. of the 3rd IEEE International Conference on Data Mining (ICDM 2003), pp. 83-90, 2003.

10.    Mining Generalized Substructures from a Set of Labeled Graphs, A. Inokuchi Proc. of the 4th IEEE International Conference on Data Mining (ICDM 2004), pp. 415-418, 2004.

11.    An Online Analytical Processing of Text Data, A. Inokuchi, K. Takeda, ACM Sixteenth Conference on Information and Knowledge Management (CIKM), 2007

12.    * Feasibility of Graph Sequence Mining based on Admissibility Constraints, A. Inokuchi and T. Washio, The Third International Workshop on Data-Mining and Statistical Science, 2008

13.    Regression with Interval Output Values, H. Kashima, K. Yamasaki, H. Saigo and A. Inokuchi, 19th International Conference on Pattern Recognition (ICPR), 2008

14.    A Fast Method to Mine Frequent Subsequences from Graph Sequence Data, A. Inokuchi and T. Washio, IEEE International Conference on Data Mining, 2008

15.    Mining Frequent Graph Sequence Patterns Induced by Vertices, Akihiro Inokuchi and Takashi Washio, Proc. of the Tenth SIAM International Conference on Data Mining, 2010

16.    GTRACE2: Improving Performance Using Labeled Union Graphs, Akihiro Inokuchi and Takashi Washio, Proc. of The 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2010


Book, Chapter in Book

1.      Kernel Methods in Computational Biology, Kernel for Graphs, H. Kashima, K. Tsuda, A. Inokuchi The MIT Press (2004), pp. 155-170.

2.      Advances in Mining Graphs, Trees and Sequences, Frontiers in Artificial Intelligence and Applications, A General Framework for Mining Frequent Subgraphs from Labeled Graphs, A. Inokuchi, T. Washio, H. Motoda, IOS Press (2005) pp.53-82

3.      New Frontiers in Artificial Intelligence: JSAI 2006 Conference and Workshops, T. Washio, K. Satoh, H. Takeda, A. Inokuchi (Eds), Springer (2007)

4.      New Frontiers in Artificial Intelligence: JSAI 2007 Conference and Workshops, Miyazaki, Japan, June 18-22, 2007, Revised Selected Papers, Satoh, K.; Inokuchi, A.; Nagao, K.; Kawamura, T. (Eds.)  Springer (2008)

5.      Advances in Knowledge Discovery and Data Mining: 12th Pacific-Asia Conference, PAKDD 2008 Osaka, Japan, May 20-23, 2008 Proceedings, T. Washio, E. Suzuki, K. M. Ting, and A. Inokuchi (Eds), Springer, 2008.

 

Other

1.      A Fast Algorithm for Mining Frequent Connected Graphs, Akihiro Inokuchi, Takashi Washio, Nishimura Yoshio and Hiroshi Motoda, IBM Research Report, RT0448, (February/2002) [pdf]


Patents

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