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2020 – today
- 2023
[j58]Takayasu Fushimi, Kazumi Saito, Hiroshi Motoda:
Constructing outlier-free histograms with variable bin-width based on distance minimization. Intell. Data Anal. 27(1): 5-29 (2023)- 2022
- [j57]Takayasu Fushimi
, Kazumi Saito, Hiroshi Motoda:
Efficient computation of expected motif frequency in uncertain graphs by exploiting possible world marginalization and motif transition. Soc. Netw. Anal. Min. 12(1): 126 (2022) - 2021
- [j56]Kazumi Saito, Takayasu Fushimi, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Efficient computation of target-oriented link criticalness centrality in uncertain graphs. Intell. Data Anal. 25(5): 1323-1343 (2021) - [j55]Takayasu Fushimi, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
General framework of opening and closing shops over a spatial network based on stochastic utility under competitive and time-bounded environment. Soc. Netw. Anal. Min. 11(1): 70 (2021) - [c137]Takayasu Fushimi, Kazumi Saito, Hiroshi Motoda:
Efficient analytical computation of expected frequency of motifs of small size by marginalization in uncertain network. ASONAM 2021: 1-8 - 2020
- [j54]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Resampling-based predictive simulation framework of stochastic diffusion model for identifying top-K influential nodes. Int. J. Data Sci. Anal. 9(2): 175-195 (2020) - [c136]Takayasu Fushimi, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Opening and Closing Dynamics of Competing Shop Groups over Spatial Networks. ASONAM 2020: 393-400 - [c135]Takayasu Fushimi, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Efficient Computing of PageRank Scores on Exact Expected Transition Matrix of Large Uncertain Graph. IEEE BigData 2020: 916-923 - [c134]Kouzou Ohara, Takayasu Fushimi, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Maximizing Network Coverage Under the Presence of Time Constraint by Injecting Most Effective k-Links. DS 2020: 421-436
2010 – 2019
- 2019
- [j53]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Critical Node Identification based on Articulation Point Detection for Uncertain Network. Int. J. Netw. Comput. 9(2): 201-216 (2019) - [c133]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Resampling-Based Framework for Unbiased Estimator of Node Centrality over Large Complex Network. DS 2019: 428-442 - [c132]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Efficient Identification of Critical Links Based on Reachability Under the Presence of Time Constraint. PRICAI (2) 2019: 404-418 - 2018
- [j52]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Which is more influential, "Who" or "When" for a user to rate in online review site? Intell. Data Anal. 22(3): 639-657 (2018) - [j51]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Accurate and efficient detection of critical links in network to minimize information loss. J. Intell. Inf. Syst. 51(2): 235-255 (2018) - [c131]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Critical Node Identification Based on Articulation Point Detection for Network with Uncertain Connectivity. CANDAR 2018: 146-152 - [c130]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Critical Link Identification Based on Bridge Detection for Network with Uncertain Connectivity. ISMIS 2018: 89-99 - [c129]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Efficient Detection of Critical Links to Maintain Performance of Network with Uncertain Connectivity. PRICAI (1) 2018: 282-295 - 2017
- [c128]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Maximizing Network Performance Based on Group Centrality by Creating Most Effective k-Links. DSAA 2017: 561-570 - [c127]Kanji Matsutani, Masahito Kumano, Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Discovering Cooperative Structure Among Online Items for Attention Dynamics. ICDM Workshops 2017: 1033-1041 - [c126]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
An Accurate and Efficient Method to Detect Critical Links to Maintain Information Flow in Network. ISMIS 2017: 116-126 - 2016
- [j50]Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Speeding-up node influence computation for huge social networks. Int. J. Data Sci. Anal. 1(1): 3-16 (2016) - [j49]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Super mediator - A new centrality measure of node importance for information diffusion over social network. Inf. Sci. 329: 985-1000 (2016) - [c125]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Accelerating Computation of Distance Based Centrality Measures for Spatial Networks. DS 2016: 376-391 - [c124]Minsoo Choy, Daehoon Kim, Jae-Gil Lee, Heeyoung Kim, Hiroshi Motoda:
Looking back on the current day: interruptibility prediction using daily behavioral features. UbiComp 2016: 1004-1015 - [c123]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Detecting Critical Links in Complex Network to Maintain Information Flow/Reachability. PRICAI 2016: 419-432 - 2015
- [j48]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Change point detection for burst analysis from an observed information diffusion sequence of tweets. J. Intell. Inf. Syst. 44(2): 243-269 (2015) - [c122]Kanji Matsutani, Masahito Kumano, Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Combining activity-evaluation information with NMF for trust-link prediction in social media. IEEE BigData 2015: 2263-2272 - [c121]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Change Point Detection for Information Diffusion Tree. Discovery Science 2015: 161-169 - [c120]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Resampling-Based Gap Analysis for Detecting Nodes with High Centrality on Large Social Network. PAKDD (1) 2015: 135-147 - [c119]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Efficient Learning of User Conformity on Review Score. SBP 2015: 182-192 - [e14]Tru H. Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu Bao Ho, David Wai-Lok Cheung, Hiroshi Motoda:
Advances in Knowledge Discovery and Data Mining - 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part I. Lecture Notes in Computer Science 9077, Springer 2015, ISBN 978-3-319-18037-3 [contents] - [e13]Tru H. Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu Bao Ho, David Wai-Lok Cheung, Hiroshi Motoda:
Advances in Knowledge Discovery and Data Mining - 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part II. Lecture Notes in Computer Science 9078, Springer 2015, ISBN 978-3-319-18031-1 [contents] - [e12]Xiaoli Li, Tru H. Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu Bao Ho, David Wai-Lok Cheung, Hiroshi Motoda:
Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2015 Workshops: BigPMA, VLSP, QIMIE, DAEBH, Ho Chi Minh City, Vietnam, May 19-21, 2015. Revised Selected Papers. Lecture Notes in Computer Science 9441, Springer 2015, ISBN 978-3-319-25659-7 [contents] - 2014
- [j47]Huan Liu, Jiawei Han, Hiroshi Motoda:
Uncovering deception in social media. Soc. Netw. Anal. Min. 4(1): 162 (2014) - [c118]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Resampling-Based Framework for Estimating Node Centrality of Large Social Network. Discovery Science 2014: 228-239 - [c117]Philip S. Yu, Masaru Kitsuregawa, Hiroshi Motoda, Bart Goethals, Minyi Guo, Longbing Cao, George Karypis, Irwin King, Wei Wang:
Welcome from DSAA 2014 chairs. DSAA 2014: 9-10 - [c116]Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Efficient analysis of node influence based on SIR model over huge complex networks. DSAA 2014: 216-222 - [c115]Keito Hatta, Masahito Kumano, Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Analyzing Mediator-Activity Effects for Trust-Network Evolution in Social Media. PRICAI 2014: 297-308 - [c114]Yuki Yamagishi, Seiya Okubo, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
A Method to Divide Stream Data of Scores over Review Sites. PRICAI 2014: 913-919 - [c113]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
A New Approach for Item Ranking Based on Review Scores Reflecting Temporal Trust Factor. SBP 2014: 161-168 - [e11]Marzena Kryszkiewicz, Chris Cornelis, Davide Ciucci, Jesús Medina-Moreno, Hiroshi Motoda, Zbigniew W. Ras:
Rough Sets and Intelligent Systems Paradigms - Second International Conference, RSEISP 2014, Held as Part of JRS 2014, Granada and Madrid, Spain, July 9-13, 2014. Proceedings. Lecture Notes in Computer Science 8537, Springer 2014, ISBN 978-3-319-08728-3 [contents] - 2013
- [j46]Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Learning to predict opinion share and detect anti-majority opinionists in social networks. J. Intell. Inf. Syst. 41(1): 5-37 (2013) - [j45]Longbing Cao, Philip S. Yu, Hiroshi Motoda, Graham J. Williams:
Special issue on behavior computing. Knowl. Inf. Syst. 37(2): 245-249 (2013) - [j44]Zhi-Hua Zhou, Wee Sun Lee, Steven C. H. Hoi, Wray L. Buntine, Hiroshi Motoda:
Introduction: special issue of selected papers of ACML 2012. Mach. Learn. 92(2-3): 221-223 (2013) - [j43]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Detecting changes in information diffusion patterns over social networks. ACM Trans. Intell. Syst. Technol. 4(3): 55:1-55:23 (2013) - [c112]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Predictive Simulation Framework of Stochastic Diffusion Model for Identifying Top-K Influential Nodes. ACML 2013: 149-164 - [c111]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Detecting changes in content and posting time distributions in social media. ASONAM 2013: 572-578 - [c110]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Identifying Super-Mediators of Information Diffusion in Social Networks. Discovery Science 2013: 170-184 - [c109]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Which Targets to Contact First to Maximize Influence over Social Network. SBP 2013: 359-367 - [e10]Hiroshi Motoda, Zhaohui Wu, Longbing Cao, Osmar R. Zaïane, Min Yao, Wei Wang:
Advanced Data Mining and Applications, 9th International Conference, ADMA 2013, Hangzhou, China, December 14-16, 2013, Proceedings, Part I. Lecture Notes in Computer Science 8346, Springer 2013, ISBN 978-3-642-53913-8 [contents] - [e9]Hiroshi Motoda, Zhaohui Wu, Longbing Cao, Osmar R. Zaïane, Min Yao, Wei Wang:
Advanced Data Mining and Applications - 9th International Conference, ADMA 2013, Hangzhou, China, December 14-16, 2013, Proceedings, Part II. Lecture Notes in Computer Science 8347, Springer 2013, ISBN 978-3-642-53916-9 [contents] - [e8]Jian Pei, Vincent S. Tseng, Longbing Cao, Hiroshi Motoda, Guandong Xu:
Advances in Knowledge Discovery and Data Mining, 17th Pacific-Asia Conference, PAKDD 2013, Gold Coast, Australia, April 14-17, 2013, Proceedings, Part I. Lecture Notes in Computer Science 7818, Springer 2013, ISBN 978-3-642-37452-4 [contents] - [e7]Jian Pei, Vincent S. Tseng, Longbing Cao, Hiroshi Motoda, Guandong Xu:
Advances in Knowledge Discovery and Data Mining, 17th Pacific-Asia Conference, PAKDD 2013, Gold Coast, Australia, April 14-17, 2013, Proceedings, Part II. Lecture Notes in Computer Science 7819, Springer 2013, ISBN 978-3-642-37455-5 [contents] - [e6]Longbing Cao, Hiroshi Motoda, Jaideep Srivastava, Ee-Peng Lim, Irwin King, Philip S. Yu, Wolfgang Nejdl, Guandong Xu, Gang Li, Ya Zhang:
Behavior and Social Computing, International Workshop on Behavior and Social Informatics, BSI 2013, Gold Coast, QLD, Australia, April 14-17, 2013 and International Workshop on Behavior and Social Informatics and Computing, BSIC 2013, Beijing, China, August 3-9, 2013, Revised Selected Papers. Lecture Notes in Computer Science 8178, Springer 2013, ISBN 978-3-319-04047-9 [contents] - 2012
- [j42]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Efficient discovery of influential nodes for SIS models in social networks. Knowl. Inf. Syst. 30(3): 613-635 (2012) - [c108]Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Burst Detection in a Sequence of Tweets Based on Information Diffusion Model. Discovery Science 2012: 239-253 - [c107]Shoko Kato, Akihiro Koide, Takayasu Fushimi, Kazumi Saito, Hiroshi Motoda:
Network Analysis of Three Twitter Functions: Favorite, Follow and Mention. PKAW 2012: 298-312 - [c106]Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Opinion Formation by Voter Model with Temporal Decay Dynamics. ECML/PKDD (2) 2012: 565-580 - [c105]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Effect of In/Out-Degree Correlation on Influence Degree of Two Contrasting Information Diffusion Models. SBP 2012: 131-138 - [c104]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Graph embedding on spheres and its application to visualization of information diffusion data. WWW (Companion Volume) 2012: 1137-1144 - [i2]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Learning Asynchronous-Time Information Diffusion Models and its Application to Behavioral Data Analysis over Social Networks. CoRR abs/1204.4528 (2012) - 2011
- [j41]Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Learning information diffusion model in a social network for predicting influence of nodes. Intell. Data Anal. 15(4): 633-652 (2011) - [c103]Takayasu Fushimi, Yamato Kubota, Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Speeding Up Bipartite Graph Visualization Method. Australasian Conference on Artificial Intelligence 2011: 697-706 - [c102]Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Detecting Anti-majority Opinionists Using Value-Weighted Mixture Voter Model. Discovery Science 2011: 150-164 - [c101]Kazumi Saito, Kouzou Ohara, Yuki Yamagishi, Masahiro Kimura, Hiroshi Motoda:
Learning Diffusion Probability Based on Node Attributes in Social Networks. ISMIS 2011: 153-162 - [c100]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Detecting Changes in Opinion Value Distribution for Voter Model. SBP 2011: 89-96 - [c99]Hiroshi Motoda:
Learning Information Diffusion Models from Observation and Its Application to Behavior Analysis. SocInfo 2011: 6 - [c98]Yuki Yamagishi, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Learning Attribute-weighted Voter Model over Social Networks. ACML 2011: 263-280 - [c97]Akihiro Koide, Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Estimating Diffusion Probability Changes for AsIC-SIS Model. ACML 2011: 297-313 - [i1]Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Efficient Detection of Hot Span in Information Diffusion from Observation. CoRR abs/1110.2659 (2011) - 2010
- [j40]Masahiro Kimura, Kazumi Saito, Ryohei Nakano, Hiroshi Motoda:
Extracting influential nodes on a social network for information diffusion. Data Min. Knowl. Discov. 20(1): 70-97 (2010) - [j39]Tu Bao Ho, Zhi-Hua Zhou, Hiroshi Motoda:
Editorial. Intell. Data Anal. 14(4): 437-438 (2010) - [c96]Masahiro Kimura, Kazumi Saito, Kouzou Ohara, Hiroshi Motoda:
Learning to Predict Opinion Share in Social Networks. AAAI 2010: 1364-1370 - [c95]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Discovery of Super-Mediators of Information Diffusion in Social Networks. Discovery Science 2010: 144-158 - [c94]Takayasu Fushimi, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda, Kouzou Ohara:
Finding Relation between PageRank and Voter Model. PKAW 2010: 208-222 - [c93]Yuya Yoshikawa, Kazumi Saito, Hiroshi Motoda, Kouzou Ohara, Masahiro Kimura:
Acquiring Expected Influence Curve from Single Diffusion Sequence. PKAW 2010: 273-287 - [c92]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Selecting Information Diffusion Models over Social Networks for Behavioral Analysis. ECML/PKDD (3) 2010: 180-195 - [c91]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Efficient Estimation of Cumulative Influence for Multiple Activation Information Diffusion Model with Continuous Time Delay. PRICAI 2010: 244-255 - [c90]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Behavioral Analyses of Information Diffusion Models by Observed Data of Social Network. SBP 2010: 149-158 - [c89]Huan Liu, Hiroshi Motoda, Rudy Setiono, Zheng Zhao:
Preface. FSDM 2010: 1-3 - [c88]Huan Liu, Hiroshi Motoda, Rudy Setiono, Zheng Zhao:
Feature Selection: An Ever Evolving Frontier in Data Mining. FSDM 2010: 4-13 - [c87]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Generative Models of Information Diffusion with Asynchronous Timedelay. ACML 2010: 193-208 - [e5]Huan Liu, Hiroshi Motoda, Rudy Setiono, Zheng Zhao:
Proceedings of the Fourth International Workshop on Feature Selection in Data Mining, FSDM, held at PAKDD 2010, Hyderabad, India, June 21st, 2010. JMLR Proceedings 10, JMLR.org 2010 [contents]
2000 – 2009
- 2009
- [j38]Tu Bao Ho, Zhi-Hua Zhou, Hiroshi Motoda:
Preface. Int. J. Softw. Informatics 3(1): 1-2 (2009) - [j37]Masahiro Kimura, Kazumi Saito, Hiroshi Motoda:
Blocking links to minimize contamination spread in a social network. ACM Trans. Knowl. Discov. Data 3(2): 9:1-9:23 (2009) - [c86]Kazumi Saito, Masahiro Kimura, Kouzou Ohara, Hiroshi Motoda:
Learning Continuous-Time Information Diffusion Model for Social Behavioral Data Analysis. ACML 2009: 322-337 - [c85]Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Discovering Influential Nodes for SIS Models in Social Networks. Discovery Science 2009: 302-316 - [c84]Masahiro Kimura, Kazumi Saito, Hiroshi Motoda:
Efficient Estimation of Influence Functions for SIS Model on Social Networks. IJCAI 2009: 2046-2051 - 2008
- [j36]Xindong Wu, Vipin Kumar, J. Ross Quinlan, Joydeep Ghosh, Qiang Yang, Hiroshi Motoda, Geoffrey J. McLachlan, Angus F. M. Ng, Bing Liu, Philip S. Yu, Zhi-Hua Zhou, Michael S. Steinbach, David J. Hand, Dan Steinberg:
Top 10 algorithms in data mining. Knowl. Inf. Syst. 14(1): 1-37 (2008) - [j35]Alexandre Termier, Marie-Christine Rousset, Michèle Sebag, Kouzou Ohara, Takashi Washio, Hiroshi Motoda:
DryadeParent, An Efficient and Robust Closed Attribute Tree Mining Algorithm. IEEE Trans. Knowl. Data Eng. 20(3): 300-320 (2008) - [c83]Masahiro Kimura, Kazumi Saito, Hiroshi Motoda:
Minimizing the Spread of Contamination by Blocking Links in a Network. AAAI 2008: 1175-1180 - [c82]Masahiro Kimura, Kazumasa Yamakawa, Kazumi Saito, Hiroshi Motoda:
Community analysis of influential nodes for information diffusion on a social network. IJCNN 2008: 1358-1363 - [c81]Kouzou Ohara, Masahiro Hara, Kiyoto Takabayashi, Hiroshi Motoda, Takashi Washio:
Pruning Strategies Based on the Upper Bound of Information Gain for Discriminative Subgraph Mining. PKAW 2008: 50-60 - [c80]Takayasu Fushimi, Takashi Kawazoe, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
What Does an Information Diffusion Model Tell about Social Network Structure?. PKAW 2008: 122-136 - [c79]Kazumi Saito, Masahiro Kimura, Hiroshi Motoda:
Effective Visualization of Information Diffusion Process over Complex Networks. ECML/PKDD (2) 2008: 326-341 - [c78]Masahiro Kimura, Kazumi Saito, Hiroshi Motoda:
Solving the Contamination Minimization Problem on Networks for the Linear Threshold Model. PRICAI 2008: 977-984 - 2007
- [j34]Fuminori Adachi, Takashi Washio, Hiroshi Motoda:
Scientific Discovery of Dynamic Models Based on Scale-type Constraints. Inf. Media Technol. 2(1): 40-52 (2007) - [j33]Takashi Washio, Koutarou Nakanishi, Hiroshi Motoda:
A Classification Method Based on Subspace Clustering and Association Rules. New Gener. Comput. 25(3): 235-245 (2007) - [c77]Hiroshi Motoda:
Pattern Discovery from Graph-Structured Data - A Data Mining Perspective. IEA/AIE 2007: 12-22 - [c76]Yang Sok Kim, Byeong Ho Kang, Paul Compton, Hiroshi Motoda:
Search engine retrieval of changing information. WWW 2007: 1195-1196 - [p1]Takashi Washio, Hiroshi Motoda:
Communicability Criteria of Law Equations Discovery. Computational Discovery of Scientific Knowledge 2007: 98-119 - 2006
- [j32]Toshiko Wakaki, Hiroyuki Itakura, Masaki Tamura, Hiroshi Motoda, Takashi Washio:
A study on rough set-aided feature selection for automatic web-page classification. Web Intell. Agent Syst. 4(4): 431-441 (2006) - [c75]Hiroshi Motoda:
What Can We Do with Graph-Structured Data? - A Data Mining Perspective. Australian Conference on Artificial Intelligence 2006: 1-2 - [c74]Kenta Fukata, Takashi Washio, Hiroshi Motoda:
A Method to Search ARX Model Orders and Its Application to Sales Dynamics Analysis. ICDM Workshops 2006: 590-595 - [c73]Takashi Washio, Yasuo Shinnou, Katsutoshi Yada, Hiroshi Motoda, Takashi Okada:
Analysis on a Relation Between Enterprise Profit and Financial State by Using Data Mining Techniques. JSAI 2006: 305-316 - [c72]Phu Chien Nguyen, Kouzou Ohara, Akira Mogi, Hiroshi Motoda, Takashi Washio:
Constructing Decision Trees for Graph-Structured Data by Chunkingless Graph-Based Induction. PAKDD 2006: 390-399 - [c71]Kiyoto Takabayashi, Phu Chien Nguyen, Kouzou Ohara, Hiroshi Motoda, Takashi Washio:
Extracting Discriminative Patterns from Graph Structured Data Using Constrained Search. PKAW 2006: 64-74 - 2005
- [j31]Akihiro Inokuchi, Takashi Washio, Hiroshi Motoda:
A General Framework for Mining Frequent Subgraphs from Labeled Graphs. Fundam. Informaticae 66(1-2): 53-82 (2005) - [j30]Warodom Geamsakul, Tetsuya Yoshida, Kouzou Ohara, Hiroshi Motoda, Hideto Yokoi, Katsuhiko Takabayashi:
Constructing a Decision Tree for Graph-Structured Data and its Applications. Fundam. Informaticae 66(1-2): 131-160 (2005) - [j29]Takashi Washio, Hiroshi Motoda, Yuji Niwa:
Enhancing the plausibility of law equation discovery through cross check among multiple scale-type-based models. J. Exp. Theor. Artif. Intell. 17(1-2): 129-143 (2005) - [j28]Fuminori Adachi, Takashi Washio, Atsushi Fujimoto, Hiroshi Motoda, Hidemitsu Hanafusa:
Multi-structure Information Retrieval Method Based on Transformation Invariance. New Gener. Comput. 23(4): 291-313 (2005) - [c70]Tetsuya Yoshida, Akira Mogi, Kouzou Ohara, Hiroshi Motoda, Takashi Washio:
Refining diagnostic knowledge extracted from interferon therapy by graph-based induction. AMT 2005: 63-68 - [c69]Tetsuya Yoshida, Hiroshi Motoda:
Performance evaluation of fusing two different knowledge sources in Ripple Down Rules method. AMT 2005: 69-74 - [c68]Tetsuya Yoshida, Ryosuke Shoda, Hiroshi Motoda:
Graph Clustering Based on Structural Similarity of Fragments. Federation over the Web 2005: 97-114 - [c67]Takashi Washio, Fuminori Adachi, Hiroshi Motoda:
SCALETRACK: A System to Discover Dynamic Law Equations Containing Hidden States and Chaos. Discovery Science 2005: 253-266 - [c66]Alexandre Termier, Marie-Christine Rousset, Michèle Sebag, Kouzou Ohara, Takashi Washio, Hiroshi Motoda:
Efficient Mining of High Branching Factor Attribute Trees. ICDM 2005: 785-788 - [c65]Takashi Washio, Yuki Mitsunaga, Hiroshi Motoda:
Mining Quantitative Frequent Itemsets Using Adaptive Density-Based Subspace Clustering. ICDM 2005: 793-796 - [c64]Takashi Washio, Fuminori Adachi, Hiroshi Motoda:
Discovering Time Differential Law Equations Containing Hidden State Variables and Chaotic Dynamics. IJCAI 2005: 1642-1644 - [c63]Takashi Washio, Koutarou Nakanishi, Hiroshi Motoda, Takashi Okada:
Mutagenicity Risk Analysis by Using Class Association Rules. JSAI Workshops 2005: 436-445 - [c62]Phu Chien Nguyen, Kouzou Ohara, Hiroshi Motoda, Takashi Washio:
Cl-GBI: A Novel Approach for Extracting Typical Patterns from Graph-Structured Data. PAKDD 2005: 639-649 - [c61]Takashi Washio, Koutarou Nakanishi, Hiroshi Motoda:
Deriving Class Association Rules Based on Levelwise Subspace Clustering. PKDD 2005: 692-700 - [c60]Takashi Washio, Atsushi Fujimoto, Hiroshi Motoda:
A Framework of Numerical Basket Analysis. SAINT Workshops 2005: 340-343 - [c59]Kenichi Yoshida, Fuminori Adachi, Takashi Washio, Hiroshi Motoda, Teruaki Homma, Akihiro Nakashima, Hiromitsu Fujikawa, Katsuyuki Yamazaki:
Memory Management of Density-Based Spam Detector. SAINT 2005: 370-376 - [e4]Shusaku Tsumoto, Takahira Yamaguchi, Masayuki Numao, Hiroshi Motoda:
Active Mining, Second International Workshop, AM 2003, Maebashi, Japan, October 28, 2003, Revised Selected Papers. Lecture Notes in Computer Science 3430, Springer 2005, ISBN 3-540-26157-5 [contents] - [e3]Achim G. Hoffmann, Hiroshi Motoda, Tobias Scheffer:
Discovery Science, 8th International Conference, DS 2005, Singapore, October 8-11, 2005, Proceedings. Lecture Notes in Computer Science 3735, Springer 2005, ISBN 3-540-29230-6 [contents] - 2004
- [j27]Huan Liu, Hiroshi Motoda, Lei Yu:
A selective sampling approach to active feature selection. Artif. Intell. 159(1-2): 49-74 (2004) - [j26]Tetsuya Yoshida, Takuya Wada, Hiroshi Motoda, Takashi Washio:
Adaptive Ripple Down Rules method based on minimum description length principle. Intell. Data Anal. 8(3): 239-265 (2004) - [j25]Kenichi Yoshida, Fuminori Adachi, Takashi Washio, Hiroshi Motoda, Teruaki Homma, Akihiro Nakashima, Hiromitsu Fujikawa, Katsuyuki Yamazaki:
Density-Based Spam Detector. IEICE Trans. Inf. Syst. 87-D(12): 2678-2688 (2004) - [j24]Nada Lavrac, Hiroshi Motoda, Tom Fawcett:
Editorial: Data Mining Lessons Learned. Mach. Learn. 57(1-2): 5-11 (2004) - [j23]Nada Lavrac, Hiroshi Motoda, Tom Fawcett, Robert Holte, Pat Langley, Pieter W. Adriaans:
Introduction: Lessons Learned from Data Mining Applications and Collaborative Problem Solving. Mach. Learn. 57(1-2): 13-34 (2004) - [c58]Kouzou Ohara, Yukio Onishi, Noboru Babaguchi, Hiroshi Motoda:
Constructive Inductive Learning Based on Meta-attributes. Discovery Science 2004: 142-154 - [c57]Warodom Geamsakul, Takashi Matsuda, Tetsuya Yoshida, Kouzou Ohara, Hiroshi Motoda, Takashi Washio, Hideto Yokoi, Katsuhiko Takabayashi:
Analysis of Hepatitis Dataset by Decision Tree Based on Graph-Based Induction. JSAI Workshops 2004: 5-28 - [c56]Masayuki Numao, Takahira Yamaguchi, Shusaku Tsumoto, Hiroshi Motoda:
Workshop on Active Mining (AM-2004). JSAI Workshops 2004: 463 - [c55]Kenichi Yoshida, Fuminori Adachi, Takashi Washio, Hiroshi Motoda, Teruaki Homma, Akihiro Nakashima, Hiromitsu Fujikawa, Katsuyuki Yamazaki:
Density-based spam detector. KDD 2004: 486-493 - [c54]Katsutoshi Yada, Hiroshi Motoda, Takashi Washio, Asuka Miyawaki:
Consumer Behavior Analysis by Graph Mining Technique. KES 2004: 800-806 - [c53]Amit Mandvikar, Huan Liu, Hiroshi Motoda:
Compact Dual Ensembles for Active Learning. PAKDD 2004: 293-297 - [c52]Phu Chien Nguyen, Takashi Washio, Kouzou Ohara, Hiroshi Motoda:
Using a Hash-Based Method for Apriori-Based Graph Mining. PKDD 2004: 349-361 - 2003
- [j22]Akihiro Inokuchi, Takashi Washio, Hiroshi Motoda:
Complete Mining of Frequent Patterns from Graphs: Mining Graph Data. Mach. Learn. 50(3): 321-354 (2003) - [j21]Takashi Washio, Hiroshi Motoda:
State of the art of graph-based data mining. SIGKDD Explor. 5(1): 59-68 (2003) - [j20]Setsuo Arikawa, Koichi Furukawa, Shinichi Morishita, Hiroshi Motoda:
Preface. Theor. Comput. Sci. 292(2): 343-344 (2003) - [c51]Shusaku Tsumoto, Takahira Yamaguchi, Masayuki Numao, Hiroshi Motoda:
Active Mining Project: Overview. Active Mining 2003: 1-10 - [c50]Warodom Geamsakul, Tetsuya Yoshida, Kouzou Ohara, Hiroshi Motoda, Takashi Washio, Hideto Yokoi, Katsuhiko Takabayashi:
Extracting Diagnostic Knowledge from Hepatitis Dataset by Decision Tree Graph-Based Induction. Active Mining 2003: 126-151 - [c49]Warodom Geamsakul, Takashi Matsuda, Tetsuya Yoshida, Hiroshi Motoda, Takashi Washio:
Performance Evaluation of Decision Tree Graph-Based Induction. Discovery Science 2003: 128-140 - [c48]Fuminori Adachi, Takashi Washio, Hiroshi Motoda, Atsushi Fujimoto, Hidemitsu Hanafusa:
Development of Generic Search Method Based on Transformation Invariance. ISMIS 2003: 486-495 - [c47]Warodom Geamsakul, Takashi Matsuda, Tetsuya Yoshida, Hiroshi Motoda, Takashi Washio:
Classifier Construction by Graph-Based Induction for Graph-Structured Data. PAKDD 2003: 52-62 - [c46]Huan Liu, Lei Yu, Manoranjan Dash, Hiroshi Motoda:
Active Feature Selection Using Classes. PAKDD 2003: 474-485 - 2002
- [j19]Takashi Matsuda, Hiroshi Motoda, Takashi Washio:
Graph-based induction and its applications. Adv. Eng. Informatics 16(2): 135-143 (2002) - [j18]Huan Liu, Hiroshi Motoda:
On Issues of Instance Selection. Data Min. Knowl. Discov. 6(2): 115-130 (2002) - [j17]Masahiro Terabe, Takashi Washio, Hiroshi Motoda, Osamu Katai, Tetsuo Sawaragi:
Attribute Generation Based on Association Rules. Knowl. Inf. Syst. 4(3): 329-349 (2002) - [c45]Takashi Matsuda, Hiroshi Motoda, Tetsuya Yoshida, Takashi Washio:
Mining Patterns from Structured Data by Beam-Wise Graph-Based Induction. Discovery Science 2002: 422-429 - [c44]Takashi Washio, Hiroshi Motoda:
Toward the Discovery of First Principle Based Scientific Law Equations. Progress in Discovery Science 2002: 553-564 - [c43]Tetsuya Yoshida, Hiroshi Motoda, Takashi Washio:
Adaptive Ripple Down Rules Method based on Minimum Description Length Principle. ICDM 2002: 530-537 - [c42]Huan Liu, Hiroshi Motoda, Lei Yu:
Feature Selection with Selective Sampling. ICML 2002: 395-402 - [c41]Takuya Wada, Tetsuya Yoshida, Hiroshi Motoda, Takashi Washio:
Extension of the RDR Method That Can Adapt to Environmental Changes and Acquire Knowledge from Both Experts and Data. PRICAI 2002: 218-227 - [c40]Keisei Fujiwara, Tetsuya Yoshida, Hiroshi Motoda, Takashi Washio:
Case Generation Method for Constructing an RDR Knowledge Base. PRICAI 2002: 228-237 - [c39]Takashi Matsuda, Hiroshi Motoda, Tetsuya Yoshida, Takashi Washio:
Knowledge Discovery from Structured Data by Beam-Wise Graph-Based Induction. PRICAI 2002: 255-264 - 2001
- [j16]Takuya Wada, Tadashi Horiuchi, Hiroshi Motoda, Takashi Washio:
A Description Length-Based Decision Criterion for Default Knowledge in the Ripple Down Rules Method. Knowl. Inf. Syst. 3(2): 146-167 (2001) - [c38]Takashi Washio, Hiroshi Motoda, Yuji Niwa:
Discovering Admissible Simultaneous Equation Models from Observed Data. ECML 2001: 539-551 - [c37]Masahiro Terabe, Takashi Washio, Hiroshi Motoda:
S3Bagging: Fast Classifier Induction Method with Subsampling and Bagging. IDA 2001: 177-186 - [c36]Takayuki Ikeda, Takashi Washio, Hiroshi Motoda:
Basket Analysis on Meningitis Data. JSAI Workshops 2001: 516-524 - [c35]Takuya Wada, Hiroshi Motoda, Takashi Washio:
Knowledge Acquisition from Both Human Expert and Data. PAKDD 2001: 550-561 - [c34]Makoto Tsukada, Takashi Washio, Hiroshi Motoda:
Automatic Web-Page Classification by Using Machine Learning Methods. Web Intelligence 2001: 303-313 - 2000
- [j15]Hiroshi Motoda, Setsuo Arikawa:
Special Feature on Discovery Science. New Gener. Comput. 18(1): 13-16 (2000) - [c33]Takashi Matsuda, Tadashi Horiuchi, Hiroshi Motoda, Takashi Washio:
Graph-Based Induction for General Graph Structured Data and Its Application to Chemical Compound Data. Discovery Science 2000: 99-111 - [c32]Takashi Washio, Hiroshi Motoda, Yuji Niwa:
Enhancing the Plausibility of Law Equation Discovery. ICML 2000: 1127-1134 - [c31]Manoranjan Dash, Huan Liu, Hiroshi Motoda:
Consistency Based Feature Selection. PAKDD 2000: 98-109 - [c30]Takashi Matsuda, Tadashi Horiuchi, Hiroshi Motoda, Takashi Washio:
Extension of Graph-Based Induction for General Graph Structured Data. PAKDD 2000: 420-431 - [c29]Akihiro Inokuchi, Takashi Washio, Hiroshi Motoda:
An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data. PKDD 2000: 13-23
1990 – 1999
- 1999
- [c28]Manoranjan Dash, Huan Liu, Hiroshi Motoda:
Feature Selection Using Consistency Measure. Discovery Science 1999: 319-320 - [c27]Akihiro Inokuchi, Takashi Washio, Hiroshi Motoda:
Derivation of the Topology Structure from Massive Graph Data. Discovery Science 1999: 330-332 - [c26]Takashi Matsuda, Tadashi Horiuchi, Hiroshi Motoda, Takashi Washio, Kohei Kumazawa, Naohide Arai:
Graph-Based Induction for General Graph Structured Data. Discovery Science 1999: 340-342 - [c25]Takashi Washio, Hiroshi Motoda, Yuji Niwa:
Discovering Admissible Model Equations from Observed Data Based on Scale-Types and Identity Constrains. IJCAI 1999: 772-779 - [c24]Hiroshi Motoda:
Computer Assisted Discovery of First Principle Equations from Numeric Data (Abstract). PAKDD 1999: 2 - [c23]Masahiro Terabe, Osamu Katai, Tetsuo Sawaragi, Takashi Washio, Hiroshi Motoda:
A Data Pre-processing Method Using Association Rules of Attributes for Improving Decision Tree. PAKDD 1999: 143-147 - [c22]Takuya Wada, Tadashi Horiuchi, Hiroshi Motoda, Takashi Washio:
Characterization of Default Knowledge in Ripple Down Rules Method. PAKDD 1999: 284-295 - [c21]Akihiro Inokuchi, Takashi Washio, Hiroshi Motoda, Kouhei Kumasawa, Naohide Arai:
Basket Analysis for Graph Structured Data. PAKDD 1999: 420-431 - 1998
- [b1]Huan Liu, Hiroshi Motoda:
Feature Selection for Knowledge Discovery and Data Mining. The Springer International Series in Engineering and Computer Science 454, Kluwer 1998, ISBN 978-1-4613-7604-0, pp. 1-214 - [j14]Hiroshi Motoda, Kenichi Yoshida:
Machine Learning Techniques to Make Computers Easier to Use. Artif. Intell. 103(1-2): 295-321 (1998) - [j13]Huan Liu, Hiroshi Motoda:
Guest Editors' Introduction: Feature Transformation and Subset Selection. IEEE Intell. Syst. 13(2): 26-28 (1998) - [j12]Hing-Yan Lee, Hongjun Lu, Hiroshi Motoda:
Knowledge discovery and data mining. Knowl. Based Syst. 10(7): 401-402 (1998) - [j11]Takashi Washio, Hiroshi Motoda:
Discovery of first-principle equations based on scale-type-based and data-driven reasoning. Knowl. Based Syst. 10(7): 403-411 (1998) - [c20]Takashi Washio, Hiroshi Motoda:
Discovering Admissible Simultaneous Equations of Large Scale Systems. AAAI/IAAI 1998: 189-196 - [c19]Takashi Washio, Hiroshi Motoda:
Development of SDS2: Smart Discovery System for Simultaneous Equation Systems. Discovery Science 1998: 352-363 - [c18]Huan Liu, Hiroshi Motoda, Manoranjan Dash:
A Monotonic Measure for Optimal Feature Selection. ECML 1998: 101-106 - [c17]Takashi Washio, Hiroshi Motoda:
Mining Association Rules for Estimation and Prediction. PAKDD 1998: 417-419 - [e2]Setsuo Arikawa, Hiroshi Motoda:
Discovery Science, First International Conference, DS '98, Fukuoka, Japan, December 14-16, 1998, Proceedings. Lecture Notes in Computer Science 1532, Springer 1998, ISBN 3-540-65390-2 [contents] - [e1]Hing-Yan Lee, Hiroshi Motoda:
PRICAI'98, Topics in Artificial Intelligence, 5th Pacific Rim International Conference on Artificial Intelligence, Singapore, November 22-27, 1998, Proceedings. Lecture Notes in Computer Science 1531, Springer 1998, ISBN 3-540-65271-X [contents] - 1997
- [j10]Byeong Ho Kang, Kenichi Yoshida, Hiroshi Motoda, Paul Compton:
Help Desk System with Intelligent Interface. Appl. Artif. Intell. 11(7-8): 611-631 (1997) - [c16]Takashi Washio, Hiroshi Motoda:
Discovering Admissible Models of Complex Systems Based on Scale-Types and Idemtity Constraints. IJCAI (2) 1997: 810-819 - [c15]Hiroshi Motoda, Kenichi Yoshida:
Machine Learning Techniques to Make Computers Easier to Use. IJCAI 1997: 1622-1631 - 1996
- [j9]Kenichi Yoshida, Hiroshi Motoda:
Automated user modeling for intelligent interface. Int. J. Hum. Comput. Interact. 8(3): 237-258 (1996) - [c14]Takashi Washio, Hiroshi Motoda:
A History-Oriented Envisioning Method. PRICAI 1996: 312-323 - [c13]Shingo Nishioka, Atsuo Kawaguchi, Hiroshi Motoda:
Process Labeled Kernel Profiling: A New Facility to Profile System Activities. USENIX ATC 1996: 295-306 - 1995
- [j8]Kenichi Yoshida, Hiroshi Motoda:
CLIP: Concept Learning from Inference Patterns. Artif. Intell. 75(1): 63-92 (1995) - [j7]Riichiro Mizoguchi, Hiroshi Motoda:
Expert Systems Research in Japan. IEEE Expert 10(4): 14-23 (1995) - [c12]Kenichi Yoshida, Hiroshi Motoda:
Tables, Graphs and Logic for Induction. Machine Intelligence 15 1995: 298-311 - [c11]Atsuo Kawaguchi, Shingo Nishioka, Hiroshi Motoda:
A Flash-Memory Based File System. USENIX 1995: 155-164 - 1994
- [j6]Masaki Suwa, Hiroshi Motoda:
PCLEARN: A Computer Model for Learning Perceptual Chunks. AI Commun. 7(2): 114-125 (1994) - [j5]Kenichi Yoshida, Hiroshi Motoda, Nitin Indurkhya:
Graph-based induction as a unified learning framework. Appl. Intell. 4(3): 297-316 (1994) - [c10]N. Hari Narayanan, Masaki Suwa, Hiroshi Motoda:
How Things Appear to Work: Predicting Behaviors from Device Diagrams. AAAI 1994: 1161-1167 - 1993
- [c9]Makoto Iwayama, Nitin Indurkhya, Hiroshi Motoda:
A New Algorithm for Automatic Configuration of Hidden Markov Models. ALT 1993: 237-250 - [c8]Kenichi Yoshida, Hiroshi Motoda, Nitin Indurkhya:
Unifying Learning Methods by Colored Digraphs. ALT 1993: 342-355 - [c7]Masaki Suwa, Hiroshi Motoda:
A Perceptual Criterion for Visually Controlling Learning. ALT 1993: 356-369 - [c6]Masaki Suwa, Hiroshi Motoda:
On dealing with dynamic utility of learned knowledge. Machine Intelligence 14 1993: 113- - 1992
- [c5]Masaki Suwa, Hiroshi Motoda:
Learning Perceptually Chunked Macro Operators. Machine Intelligence 13 1992: 419-440 - 1991
- [j4]Hiroshi Motoda, Riichiro Mizoguchi, John H. Boose, Brian R. Gaines:
Knowledge Acquisition for Knowledge-Based Systems. IEEE Expert 6(4): 53-64 (1991) - [j3]Atsuo Kawaguchi, Hiroshi Motoda, Riichiro Mizoguchi:
Interview-Based Knowledge Acquisition Using Dynamic Analysis. IEEE Expert 6(5): 47-60 (1991) - [c4]Masaki Suwa, Hiroshi Motoda:
The use of abstract primitives in representing the meanings of "Verbs" for understanding metaphors. ALT 1991: 231-242 - 1990
- [j2]Hiroshi Motoda:
The Current Status of Expert System Development and Related Technologies in Japan. IEEE Expert 5(4): 3-11 (1990)
1980 – 1989
- 1989
- [j1]Masaki Suwa, Hiroshi Motoda:
Acquisition of associative knowledge by the frustration-based learning method in an auxiliary-line problem. Knowl. Acquis. 1(1): 113-137 (1989) - 1988
- [c3]Akito Sakurai, Hiroshi Motoda:
Proving Definite Clauses without Explicit Use of Inductions. LP 1988: 11-26 - 1984
- [c2]Hiroshi Motoda, Naoyuki Yamada, Kenichi Yoshida:
A Knowledge based System for Plant Diagnosis. FGCS 1984: 582-588 - 1983
- [c1]Naoyuki Yamada, Hiroshi Motoda:
A Diagnosis Method of Dynamic System Using the Knowledge on System Description. IJCAI 1983: 225-229
Coauthor Index
[j56] [j55] [j54] [c136] [c135] [c134] [j53] [c133] [c132] [j52] [j51] [c131] [c130] [c129] [c128] [c127] [c126] [j50] [j49] [c125] [c123] [j48] [c122] [c121] [c120] [c119] [c118] [c116] [c115] [c114] [c113] [j46] [j43] [c112] [c111] [c110] [c109] [j42] [c108] [c106] [c105] [c104] [i2] [j41] [c103] [c102] [c101] [c100] [c98] [c97] [i1] [j40] [c96] [c95] [c94] [c93] [c92] [c91] [c90] [c87] [j37] [c86] [c85] [c84] [c83] [c82] [c80] [c79] [c78]
[j56] [j55] [j54] [c136] [c135] [c134] [j53] [c133] [c132] [j52] [j51] [c131] [c130] [c129] [c128] [c127] [c126] [j50] [j49] [c125] [c123] [j48] [c122] [c121] [c120] [c119] [c118] [c116] [c115] [c114] [c113] [j46] [j43] [c112] [c111] [c110] [c109] [j42] [c108] [c106] [c105] [c104] [i2] [j41] [c103] [c102] [c101] [c100] [c98] [c97] [i1] [c96] [c95] [c94] [c93] [c92] [c91] [c90] [c87] [c86] [j35] [c81] [c72] [c71] [j30] [c70] [c66] [c62] [c58] [c57] [c52] [c50]
[j58] [j57] [j56] [j55] [c137] [j54] [c136] [c135] [c134] [j53] [c133] [c132] [j52] [j51] [c131] [c130] [c129] [c128] [c127] [c126] [j50] [j49] [c125] [c123] [j48] [c122] [c121] [c120] [c119] [c118] [c116] [c115] [c114] [c113] [j46] [j43] [c112] [c111] [c110] [c109] [j42] [c108] [c107] [c106] [c105] [c104] [i2] [j41] [c103] [c102] [c101] [c100] [c98] [c97] [i1] [j40] [c96] [c95] [c94] [c93] [c92] [c91] [c90] [c87] [j37] [c86] [c85] [c84] [c83] [c82] [c80] [c79] [c78]
[j35] [c81] [j34] [j33] [p1] [j32] [c74] [c73] [c72] [c71] [j31] [j29] [j28] [c70] [c67] [c66] [c65] [c64] [c63] [c62] [c61] [c60] [c59] [j26] [j25] [c57] [c55] [c54] [c52] [j22] [j21] [c50] [c49] [c48] [c47] [j19] [j17] [c45] [c44] [c43] [c41] [c40] [c39] [j16] [c38] [c37] [c36] [c35] [c34] [c33] [c32] [c30] [c29] [c27] [c26] [c25] [c23] [c22] [c21] [j11] [c20] [c19] [c17] [c16] [c14]
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