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Tomonobu Ozaki
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2020 – today
- 2024
- [c55]Yuta Tanaka, Tomonobu Ozaki:
Interactive construction of personalized fashion capsule wardrobes with alternative item recommendations. ICICT 2024: 493-498 - 2022
- [c54]Ryu Hashimoto, Tomonobu Ozaki:
Extraction of Preference and Classification Rules in Floor Plan Databases using Answer Set Programming. CANDARW 2022: 97-102 - [c53]Rento Kurokochi, Tomonobu Ozaki:
Rule-based role estimation in werewolf games using probabilistic logic programming. CANDARW 2022: 114-119 - [c52]Yuta Tanaka, Tomonobu Ozaki:
An extension of optimal fashion capsule wardrobe construction by considering visual dissimilarity and number of good coordinates. CANDARW 2022: 224-228 - 2021
- [c51]Kota Matsuyama, Tomonobu Ozaki:
Heuristic extraction of co-occurrence patterns for effective construction of graph-based interpretable decision sets. CANDAR (Workshops) 2021: 159-165 - [c50]Kenta Shimada, Tomonobu Ozaki:
Adversarial attack detection on node classification by autoencoder-based analysis of hidden layers in graph convolutional networks. CANDAR (Workshops) 2021: 173-179 - 2020
- [c49]Akari Ninomiya, Tomonobu Ozaki:
Cooking Recipe Analysis based on Sequences of Distributed Representation on Procedure Texts and Associated Images. CEA@ISMR 2020: 13-18 - [c48]Kota Matsuyama, Tomonobu Ozaki:
Extraction of Interpretable Decision Sets in Graph Databases. CANDAR 2020: 153-159
2010 – 2019
- 2019
- [j7]Tomonobu Ozaki
, Randy Goebel, Katsumi Inoue
From Fifth Generation Computing to Skill Science - A Biographical Essay of Koichi Furukawa. New Gener. Comput. 37(2): 141-158 (2019) - [c47]Tomonobu Ozaki:
Evaluation Measures for Extended Association Rules Based on Distributed Representations. AINA Workshops 2019: 305-313 - [c46]Kazuki Sato, Tomonobu Ozaki:
Estimation of Emotion Type and Intensity in Japanese Tweets Using Multi-task Deep Learning. AINA Workshops 2019: 314-323 - [c45]Akari Ninomiya, Tomonobu Ozaki:
Learning Distributed Representation of Recipe Flow Graphs via Frequent Subgraphs. CEA@ICMR 2019: 25-28 - [c44]Takuya Namiki, Tomonobu Ozaki:
Representation of Recipe Flow Graphs in Succinct Data Structures. CEA@ICMR 2019: 29-32 - [c43]Tomonobu Ozaki:
Extraction of Characteristic Subgraph Patterns with Support Threshold from Databases of Floor Plans. CANDAR 2019: 197-203 - 2018
- [c42]Saki Kawanobe, Tomonobu Ozaki:
Experimental Study of Characterizing Frequent Itemsets Using Representation Learning. AINA Workshops 2018: 170-174 - [c41]Tomonobu Ozaki:
Evaluation Measures for Frequent Itemsets Based on Distributed Representations. CANDAR 2018: 153-159 - 2017
- [c40]Yosuke Suzuki, Tomonobu Ozaki:
Stacked Denoising Autoencoder-Based Deep Collaborative Filtering Using the Change of Similarity. AINA Workshops 2017: 498-502 - [c39]Tomonobu Ozaki, Xia Gao, Mako Mizutani:
Extraction of Characteristic Sets of Ingredients and Cooking Actions on Cuisine Type. AINA Workshops 2017: 509-513 - [c38]Saki Kawanobe, Tomonobu Ozaki:
Extraction of Characteristic Frequent Visual Patterns by Distributed Representation. AINA Workshops 2017: 525-530 - [c37]Tatsuya Toki, Tomonobu Ozaki:
Discovery of δ-Tolerance Closed Subgraphs on GPGPU. CANDAR 2017: 173-179 - 2016
- [c36]Tatsuya Toki, Tomonobu Ozaki:
Experimental Evaluation of a GPU-based Frequent Subgraph Miner Using Synthetic Databases. CANDAR 2016: 504-507 - [c35]Ema Nishizaki, Tomonobu Ozaki:
Behavior Analysis of Executed and Attacked Players in Werewolf Game by ILP. ILP (Short Papers) 2016: 48-53 - [c34]Saki Sakaguchi, Tomonobu Ozaki:
An Experimental Analysis of Whispers' Effect in Werewolf BBS by Relational Association Rules. ILP (Short Papers) 2016: 60-65 - 2015
- [c33]Koichi Furukawa, Keita Kinjo
The Cognitive Role of Analogical Abduction in Skill Acquisition. JSAI-isAI Workshops 2015: 499-513 - 2013
- [c32]Koichi Furukawa, Keita Kinjo, Tomonobu Ozaki, Makoto Haraguchi:
On Skill Acquisition Support by Analogical Rule Abduction. ISIP 2013: 71-83 - 2012
- [c31]Tomonobu Ozaki, Minoru Etoh:
Social Network Discovery from Multiple Log Data through a Behavior Model. AINA Workshops 2012: 863-868 - 2011
- [j6]Hiroyuki Monji, Satoshi Koizumi, Tomonobu Ozaki, Takenao Ohkawa:
Interaction site prediction by structural similarity to neighboring clusters in protein-protein interaction networks. BMC Bioinform. 12(S-1): S39 (2011) - [j5]Riku Kyogoku, Ryo Fujimoto, Tomonobu Ozaki, Takenao Ohkawa:
A method for supporting retrieval of articles on protein structure analysis considering users' intention. BMC Bioinform. 12(S-1): S42 (2011) - [c30]Tomonobu Ozaki, Minoru Etoh:
Social Network Inference of Smartphone Users Based on Information Diffusion Models. ADMA (2) 2011: 304-317 - [c29]Tomonobu Ozaki, Minoru Etoh:
Closed and Maximal Subgraph Mining in Internally and Externally Weighted Graph Databases. AINA Workshops 2011: 626-631 - [c28]Tomonobu Ozaki, Minoru Etoh:
Estimation of Implicit user Influence from Proxy Logs - An Empirical Study on the Effects of Time Difference and Popularity. KDIR 2011: 250-255 - [c27]Tomonobu Ozaki, Minoru Etoh:
Correlation and Contrast Link Formation Patterns in a Time Evolving Graph. ICDM Workshops 2011: 1147-1154 - 2010
- [j4]Kazunori Miyanishi, Tomonobu Ozaki, Takenao Ohkawa:
A Method to Extract Sentences Containing Protein Function Information with Training Data Extension Based on User's Feedback. Inf. Media Technol. 5(4): 1278-1286 (2010) - [c26]Kazunori Miyanishi, Tomonobu Ozaki, Takenao Ohkawa:
A Method to Identify Protein Names with Iterative Extension of Training Data Set. BICoB 2010: 178-183
2000 – 2009
- 2009
- [j3]Yuta Ashida, Tomonobu Ozaki, Takenao Ohkawa:
A Comparative Analysis of Metabolic Pathways Based on Metabolic Steady States. Inf. Media Technol. 4(4): 885-894 (2009) - [j2]Kazunori Miyanishi, Tomonobu Ozaki, Takenao Ohkawa:
Selection of Effective Sentences from a Corpus to Improve the Accuracy of Identification of Protein Names. Inf. Media Technol. 4(4): 895-902 (2009) - [c25]Tomonobu Ozaki, Takenao Ohkawa:
Discovery of Correlated Sequential Subgraphs from a Sequence of Graphs. ADMA 2009: 265-276 - [c24]Fumiya Nakagaito, Tomonobu Ozaki, Takenao Ohkawa:
Discovery of Quantitative Sequential Patterns from Event Sequences. ICDM Workshops 2009: 31-36 - [c23]Masaki Shinoda, Tomonobu Ozaki, Takenao Ohkawa:
Weighted Frequent Subgraph Mining in Weighted Graph Databases. ICDM Workshops 2009: 58-63 - [c22]Yuuki Miyoshi, Tomonobu Ozaki, Takenao Ohkawa:
Frequent Pattern Discovery from a Single Graph with Quantitative Itemsets. ICDM Workshops 2009: 527-532 - [c21]Tomonobu Ozaki, Takenao Ohkawa:
Efficient Discovery of Closed Hyperclique Patterns in Multidimensional Structured Databases. ICDM Workshops 2009: 533-538 - 2008
- [c20]Tomonobu Ozaki, Takenao Ohkawa:
Mining Correlated Pairs of Patterns in Multidimensional Structured Databases. ICDM Workshops 2008: 275-282 - [c19]Tsubasa Yamamoto, Tomonobu Ozaki, Takenao Ohkawa:
Discovery of Internal and External Hyperclique Patterns in Complex Graph Databases. ICDM Workshops 2008: 301-309 - [c18]Tomonobu Ozaki, Takenao Ohkawa:
Mining Mutually Dependent Ordered Subtrees in Tree Databases. PAKDD Workshops 2008: 75-86 - [c17]Tomonobu Ozaki, Takenao Ohkawa:
Mining Correlated Subgraphs in Graph Databases. PAKDD 2008: 272-283 - [c16]Satoshi Koizumi, Keisuke Imada, Tomonobu Ozaki, Takenao Ohkawa:
Extraction of Binding Sites in Proteins by Searching for Similar Local Molecular Surfaces. PRIB 2008: 87-97 - 2007
- [c15]Tsubasa Yamamoto, Tomonobu Ozaki, Takenao Ohkawa:
Discovery of Frequent Graph Patterns that Consist of the Vertices with the Complex Structures. MCD 2007: 143-156 - [c14]Yasuhiro Kiuchi, Tomonobu Ozaki, Takenao Ohkawa:
Partial Geometric Hashing for Retrieving Similar Interaction Protein Using Profile. ITNG 2007: 589-596 - [c13]Tomonobu Ozaki, Takenao Ohkawa:
Efficiently Mining Closed Constrained Frequent Ordered Subtrees by Using Border Information. PAKDD 2007: 745-752 - 2006
- [c12]Hitohiro Shiozaki, Tomonobu Ozaki, Takenao Ohkawa:
Mining Closed and Maximal Frequent Induced Free Subtrees. ICDM Workshops 2006: 14-18 - [c11]Tomoki Watanuma, Tomonobu Ozaki, Takenao Ohkawa:
Decision Tree Construction from Multidimensional Structured Data. ICDM Workshops 2006: 237-241 - [c10]Tomonobu Ozaki, Takenao Ohkawa:
Efficient Mining of Closed Induced Ordered Subtrees in Tree-structured Databases. ICDM Workshops 2006: 279-283 - 2002
- [c9]Ikuo Kobayashi, Koichi Furukawa, Tomonobu Ozaki, Mutsumi Imai:
A Computational Model for Children's Language Acquisition Using Inductive Logic Programming. Progress in Discovery Science 2002: 140-155 - [c8]Soh Igarashi, Tomonobu Ozaki, Koichi Furukawa:
Respiration Reflecting Musical Expression: Analysis of Respiration during Musical Performance by Inductive Logic Programming. ICMAI 2002: 94-106 - 2001
- [j1]Ikuo Kobayashi, Koichi Furukawa, Tomonobu Ozaki, Mutsumi Imai:
A Bootstrapping Model for Children's Vocabulary Acquisition using Inductive Logic Programming. Electron. Trans. Artif. Intell. 5(B): 47-72 (2001) - [c7]Tomonobu Ozaki, Koichi Furukawa:
Application of Pruning Techniques for Propositional Learning to Progol. ILP 2001: 206-219 - 2000
- [c6]Koichi Furukawa, Tomonobu Ozaki:
On the Completion of Inverse Entailment for Mutual Recursion and its Application to Self Recursion. ILP Work-in-progress reports 2000
1990 – 1999
- 1999
- [c5]Koichi Furukawa, Ikuo Kobayashi, Tomonobu Ozaki, Mutsumi Imai:
A Model of Children's Vocabulary Acquisition Using Inductive Logic Programming. Discovery Science 1999: 321-322 - 1997
- [c4]Koichi Furukawa, Tomonobu Ozaki, Tomoko Murakami, Ken Ueno, Keiko Shimazu:
Query Evaluation of Deductive Database by MGTP and its Application to Data Mining. DDLP 1997 - [c3]Koichi Furukawa, Tomoko Murakami, Ken Ueno, Tomonobu Ozaki, Keiko Shimazu:
On a Sufficient Condition for the Existence of Most Specific Hypothesis in Progol. ILP 1997: 157-164 - [c2]Tomonobu Ozaki, Koichi Furukawa, Tomoko Murakami, Ken Ueno:
Realizing Progol by Forward Reasoning. ILP 1997: 227-234 - 1996
- [c1]Hiroshi Fujita, Naoki Yagi, Tomonobu Ozaki, Koichi Furukawa:
A New Design and Implementation of Progol by Bottom-Up Computation. Inductive Logic Programming Workshop 1996: 163-174
Coauthor Index
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