Publication

Journal

International Conference (Peer-reviewed)

  • Y. Ishii, A. Sugiyama, K. Fukushima, R. Okada, and T. Nakanishi, “A Learning Enhancement System for Learner’s Community,” in R. Lee (Ed.), Software Engineering and Management: Theory and Application, Studies in Computational Intelligence, vol. 1137, Springer, Cham, pp. 15, 2024. https://doi.org/10.1007/978-3-031-55174-1_15.

  • R. Ohnishi, R. Okada, Y. Murakami, T. Nakanishi, T. Ozawa, Y. Ogasawara, K. Ohashi., “Visualization of Members’ Activities in a Series of Group Works by Time-series Feature Comparison Method,” 2023 15th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter), Bali, Indonesia, 2024, pp. 69-74, https://doi.org/10.1109/IIAI-AAI-Winter61682.2023.00021.
  • M. Momozawa, R. Okada, A. Minematsu and T. Nakanishi, “Off-Rhythm Detection System for Beginner Violinists,” 2023 15th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter), Bali, Indonesia, 2024, pp. 360-365, https://doi.org/10.1109/IIAI-AAI-Winter61682.2023.00072.
  • R. Fukui, R. Okada, A. Minematsu and T. Nakanishi, “Country by Country Comparison of Thumbnail Features Contributing to Views Using AIME for YouTube,” 2023 15th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter), Bali, Indonesia, 2024, pp. 342-347, https://doi.org/10.1109/IIAI-AAI-Winter61682.2023.00069.
  • A. Minematsu and T. Nakanishi, “A Factor Extraction of Preference in Musical Performances Using AIME with Focus on Time-Series Derivative Features,” 2023 15th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter), Bali, Indonesia, 2024, pp. 312-317, https://doi.org/10.1109/IIAI-AAI-Winter61682.2023.00064.[Competitive Paper Award]
  • A. Sugiyama, R. Okada, A. Minematsu and T. Nakanishi, “A Complexity Feature Extraction Method by Chord Progression and Transition Density for Music Media Content,” 2023 15th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter), Bali, Indonesia, 2024, pp. 187-192, https://doi.org/10.1109/IIAI-AAI-Winter61682.2023.00043.
  • Y.Ohkawa, T.Nakanishi, Anomaly Detection Through Graph Autoencoder Based Learning of Screenshot Image Logs, In Proceedings of 2024 IEEE 18th International Conference on Semantic Computing (ICSC), pp.65-68, 2024, https://doi.org/10.1109/ICSC59802.2024.00016.
  • T. Ohno, Y.Hoshino, T. Nakanishi, Temporal Analysis of Editorial Trends in Major Newspapers Following the Prime Minister’s Speech, In Proceedings of 2024 IEEE 18th International Conference on Semantic Computing (ICSC), pp.148-151, 2024, https://doi.org/10.1109/ICSC59802.2024.00029.
  • F. Cheng and T. Nakanishi, “A Keyword Transition Extraction Method for Time-series Text Data and Its Application to Discovering the Transition of Key Technology Elements in Japan,” 2023 14th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), Koriyama, Japan, pp. 100-105, 2023. https://doi.org/10.1109/IIAI-AAI59060.2023.00029
  • R. Ohnishi, Y. Murakami, T. Nakanishi, R. Okada, T. Ozawa, K. Fukushima, T. Miyamae, Y. Ogasawara, K. Akiyama, K. Ohashi, Time-Series Multidimensional Dialogue Feature Visualization Method for Group Work. In: Lee, R. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2022-Winter. Studies in Computational Intelligence, vol 1086. Springer, Cham., 2023. https://doi.org/10.1007/978-3-031-26135-0_6
  • K. Komiya, R. Okada, A. Minematsu, T. Nakanishi, Automatic Piano Accompaniment Generation Method by Drum Rhythm Features with Selectable Difficulty Level. In: Lee, R. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2022-Winter. Studies in Computational Intelligence, vol 1086. Springer, Cham., 2023. https://doi.org/10.1007/978-3-031-26135-0_2
  • T. Nitta, S. Hagimoto, K. Miyamura, R. Okada, T. Nakanishi, Time-Series Flexible Resampling for Continuous and Real-Time Finger Character Recognition, 2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT’22), pp. 357-363, February 2023. https://doi.org/10.1109/WI-IAT55865.2022.00059
  • Y. Noji, R. Okada, T. Nakanishi, Represent Score as the Measurement of User Influence on Twitter. In: Lee, R. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. SNPD 2022. Studies in Computational Intelligence, vol 1074. Springer, Cham., 2023. https://doi.org/10.1007/978-3-031-19604-1_3
  • S. Hagimoto, T. Nitta, R. Okada, T. Nakanishi, A Dynamic Finger Character Recognition Method using Landmark Behavior Rule Base, in Proceedings of 2022 13th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter), pp.189-195, 2022, https://doi.org/10.1109/IIAI-AAI-Winter58034.2022.00045. [acceptance rate:37.3%]
  • S. Liu, T. Nakanishi, Obstacles Detection and Motion Estimation by using Multiple Lidar Sensors Data, in Proceedings of 2022 13th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter), pp.196-201, 2022, https://doi.org/10.1109/IIAI-AAI-Winter58034.2022.00046. [acceptance rate:37.3%]
  • K. Sano, K. Ojima, R. Okada, T. Nakanishi, A Method for Predicting Sudden/Cyclic Stress using Vital Data and the Realization of a Tracking Mental Management Robot, in Proceedings of 2022 13th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter), pp.202-207, 2022, https://doi.org/10.1109/IIAI-AAI-Winter58034.2022.00047. [acceptance rate:37.3%]
  • M. Iwamoto, K. Ojima, R. Okada, T. Nakanishi, Emotion Estimation Method by Convolutional Neural Network for Heartbeat Vital Data, in Proceedings of 2022 13th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter), pp.245-250, 2022, https://doi.org/10.1109/IIAI-AAI-Winter58034.2022.00055. [acceptance rate:37.3%] [Best Student Paper Award]
  • Y. Ohkawa, T. Nakanishi, Detection Method of User Behavior Transition on Computer. In: Chen, W., Yao, L., Cai, T., Pan, S., Shen, T., Li, X. (eds) Advanced Data Mining and Applications. ADMA 2022. Lecture Notes in Computer Science, vol 13726. Springer, Cham., 2022. https://doi.org/10.1007/978-3-031-22137-8_6
  • T. Inari, T. Nakanishi, Concentration Patterns Estimation Method in Deskwork by Using Time-series k-means, In Proceedings of 2022 International Electronics Symposium (IES), pp. 576-580, 2022. https://doi.org/10.1109/IES55876.2022.988831.
  • S. Tamaru, H. Taki, R. Usuki, T. Nakanishi, Recipe Recommendation Method by Similarity Measure with Food Image Recognition, In Proceedings of 2022 the 6th International Conference on Information System and Data Mining (ICISDM 2022). Association for Computing Machinery, New York, NY, USA, pp.81–88, 2022. https://doi.org/10.1145/3546157.3546170
  • A. Ikegami, T. Nakanishi, Interpretable Predictive Results in Classification of Waka Poets, In Proceedings of the 12th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2022), pp.436-442, 2022. https://doi.org/10.1109/IIAIAAI55812.2022.00092 [acceptance rate 33.5%]
  • H. Nakata, T. Nakanishi, Music Recommendation Method for Time-Series Emotions from Lyrics using Valence-Arousal-Dominance Model, In Proceedings of the 12th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2022), pp.443-448, 2022. https://doi.org/10.1109/IIAIAAI55812.2022.00093 [acceptance rate 33.5%] [Honorable Mention Award]
  • R. Hirano, R. Okada, T. Nakanishi, Extraction Method for Important Words as a Viewer’s Reaction Arousal Factor from YouTube – Transcription, In Proceedings of the 12th IIAI International Congress on Advanced Applied Informatics (IIAI AAI 2022), pp.651-652, 2022. https://doi.org/10.1109/IIAIAAI55812.2022.00129 (Poster Abstract)
  • Y. Ishii, T. Nakanishi, R. Okada and A. Minematsu, “Tourist Spots Recommendation Method Corresponding to Place Names Appearing in Novel Contents,” 2022 7th International Conference on Business and Industrial Research (ICBIR), pp. 192-197,2022. https://doi.org/10.1109/ICBIR54589.2022.9786468
  • K. Sano, K. Ojima, T. Nakamura, R. Okada, T. Nakanishi, A Method for Estimating Emotions Using HRV for Vital Data and Its Application to Self-mentalcare Management System, in Tokuro Matsuo (editor) Proceedings of 11th International Congress on Advanced Applied Informatics, EPiC Series in Computing, Vol 81, pp. 89–100, 2022. https://doi.org/10.29007/fp2d
  • Y. Ishii, A. Ikegami, T. Nakanishi, Realization of Discovery for Burst Topic Transition Using the Topic Change Point Detection Method for Time-Series Text Data, in Tokuro Matsuo (editor) Proceedings of 11th International Congress on Advanced Applied Informatics, EPiC Series in Computing, Vol 81, pp, 362–372, 2022. https://doi.org/10.29007/k8pb
  • A. Ikegami, R. Okada, T.Nakanishi, The Discovery of Historical Transition in Aesthetic Notions Through Changes in Co-occurrence Words Mainly Used in Waka Poetry in Three Major Poetry Anthologies. In: Lee R. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. SNPD 2021. Studies in Computational Intelligence, vol 1012. Springer, Cham, 2022. https://doi.org/10.1007/978-3-030-92317-4_12
  • H. Nakata, T. Nakanishi, Music Impression Extraction Method By chord Impressions and Its Application to Music Media Retrieval, in Proceedings of 22nd IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2021-Fall), pp.68-73, 2021, https://doi.org/10.1109/IIAIAAI55812.2022.00093.
  • K. Miyamura, R. Okada, T. Nakanishi, Mashuprium and Timeline Visualization: Implementation of 3D Space and Timeline Visualization for Automatic Mashup Creation, In Proceedings of the 10th International Congress on Applied Information Technology (IIAI AAI 2021), pp.804-809, 2021, https://doi.org/10.1109/IIAI-AAI53430.2021.00141.[acceptance rate 33.6%]
  • A. Yanase, T. Nakanishi, Musical Impression Extraction Method by Discovering Relationships between Acoustic Features and Impression Terms, In Proceedings of the 10th International Congress on Applied Information Technology (IIAI AAI 2021), pp.810-807, 2021, https://doi.org/10.1109/IIAI-AAI53430.2021.00142.[acceptance rate 33.6%] [Honorable Mention Award]
  • K. Miyamura, R. Okada, T. Nakanishi, Automatic Music Mashup Creation Method by Similarity of Features, In proceedings of 20th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2021 Summer),pp.35-40, 2021, https://doi.org/10.1109/ICIS51600.2021.9516600.
  • S. Hagimoto, T. Nitta, A. Yanase, T. Nakanishi, R. Okada, V. Sornlertlamvanich, Knowledge Base Creation by Reliability of Coordinates Detected from Videos for Finger Character Recognition, In proc. of 19th IADIS International Conference e-Society 2021, FSP 5.1-F144, pp.169-176, 2021.
  • T. Nitta, S. Hagimoto, A. Yanase, T. Nakanishi, R. Okada, V. Sornlertlamvanich, Finger Character Recognition in Sign Language Using Finger Feature Knowledge Base for Similarity Measure, In Proceedings of the 3rd IEEE/IIAI International Congress on Applied Information Technology (IEEE/IIAI AIT 2020), 2020, https://doi.org/10.1109/WI-IAT55865.2022.00059. [Best Paper Award]

Domestic Conference (non-peer-reviewed)