Makoto Imamura

According to our database, Makoto Imamura authored at least 26 papers between 1999 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

MERLIN++: parameter-free discovery of time series anomalies.

Takaaki Nakamura, Ryan Mercer, Makoto Imamura, Eamonn J. Keogh

Data Min. Knowl. Discov., March, 2023

Parameter-free Spikelet: Discovering Different Length and Warped Time Series Motifs using an Adaptive Time Series Representation.

Makoto Imamura, Takaaki Nakamura

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Matrix Profile XXX: MADRID: A Hyper-Anytime and Parameter-Free Algorithm to Find Time Series Anomalies of all Lengths.

Yue Lu, Thirumalai Vinjamoor Akhil Srinivas, Takaaki Nakamura, Makoto Imamura, Eamonn J. Keogh

Proceedings of the IEEE International Conference on Data Mining, 2023

A Symbolic Representation of Two-Dimensional Time Series for Arbitrary Length DTW Motif.

Makoto Imamura, Takaaki Nakamura

Proceedings of the IEEE International Conference on Data Mining, 2023

2021

Spikelet: An Adaptive Symbolic Approximation for Finding Higher-Level Structure in Time Series.

Makoto Imamura, Takaaki Nakamura

Proceedings of the IEEE International Conference on Data Mining, 2021

2020

Discovery of evolving companion from trajectory data streams.

Thi Thi Shein, Sutheera Puntheeranurak, Makoto Imamura

Knowl. Inf. Syst., 2020

Discovery of Loose Group Companion From Trajectory Data Streams.

Thi Thi Shein, Sutheera Puntheeranurak, Makoto Imamura

IEEE Access, 2020

Matrix Profile XXI: A Geometric Approach to Time Series Chains Improves Robustness.

Makoto Imamura, Takaaki Nakamura, Eamonn J. Keogh

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

MERLIN: Parameter-Free Discovery of Arbitrary Length Anomalies in Massive Time Series Archives.

Takaaki Nakamura, Makoto Imamura, Ryan Mercer, Eamonn J. Keogh

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019

Introducing time series chains: a new primitive for time series data mining.

Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn J. Keogh

Knowl. Inf. Syst., 2019

2018

Assessment Map for Multidisciplinary Abilities for IoT System Development Education based on a Robot Contest.

Harumi Watanabe, Mikiko Sato, Masafumi Miwa, Makoto Imamura, Shintaro Hosoai, Nobuhiko Ogura, Hiroyuki Nakamura, Kenji Hisazumi

Proceedings of the IEEE International Conference on Teaching, 2018

Time Series Chains: A Novel Tool for Time Series Data Mining.

Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn J. Keogh

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

Multidisciplinary skill assessment for embedded software development education via a robot contest.

Harumi Watanabe, Mikiko Sato, Masafumi Miwa, Makoto Imamura, Shintaro Hosoai, Nobuhiko Ogura, Hiroyuki Nakamura, Kenji Hisazumi

Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings, 2018

Compulsory Game based Robot Contest for Embedded System Development Education.

Harumi Watanabe, Mikiko Sato, Masafumi Miwa, Makoto Imamura, Shintaro Hosoai, Nobuhiko Ogura, Hiroyuki Nakamura, Kenji Hisazumi

Proceedings of the 7th International Conference on Software and Computer Applications, 2018

Exercise Guidance Generation Based on Joint Vector Model Using Kinect Sensor.

Junji Tsuda, Yudai Iimura, Makoto Imamura

Proceedings of the Eleventh International Conference on Mobile Computing and Ubiquitous Network, 2018

Efficient Discovery of Traveling Companion from Evolving Trajectory Data Stream.

Sutheera Puntheeranurak, Thi Thi Shein, Makoto Imamura

Proceedings of the 2018 IEEE 42nd Annual Computer Software and Applications Conference, 2018

2017

Matrix Profile VII: Time Series Chains: A New Primitive for Time Series Data Mining (Best Student Paper Award).

Yan Zhu, Makoto Imamura, Daniel Nikovski, Eamonn J. Keogh

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2016

Exemplar learning for extremely efficient anomaly detection in real-valued time series.

Michael Jones, Daniel Nikovski, Makoto Imamura, Takahisa Hirata

Data Min. Knowl. Discov., 2016

2012

A stream query language TPQL for anomaly detection in facility management.

Makoto Imamura, Shigenobu Takayama, Tatsuji Munaka

Proceedings of the 16th International Database Engineering & Applications Symposium, 2012

2010

A high linearity compact timing vernier for CMOS timing generator.

Jun Kohno, Tatsuro Akiyama, Dai Kato, Makoto Imamura

Proceedings of the 2011 IEEE International Test Conference, 2010

2009

A Web Application Development Framework Using Code Generation from MVC-Based UI Model.

Keisuke Watanabe, Makoto Imamura, Katsushi Asami, Toshiyuki Amanuma

Proceedings of the Distributed Computing, 2009

A Combination of Active Learning and Semi-supervised Learning Starting with Positive and Unlabeled Examples for Word Sense Disambiguation: An Empirical Study on Japanese Web Search Query.

Makoto Imamura, Yasuhiro Takayama, Nobuhiro Kaji, Masashi Toyoda, Masaru Kitsuregawa

Proceedings of the ACL 2009, 2009

2008

Term Knowledge Acquisition Using the Structure of Headline Sentences from Information Equipments Operating Manuals.

Makoto Imamura, Yasuhiro Takayama, Masanori Akiyoshi, Norihisa Komoda

Proceedings of the ICSOFT 2008, 2008

2007

A Document Rules Description Language Based on Feature Logic for XML Document Exchange.

Makoto Imamura, Yasuhiro Takayama, Yasuhiro Okada, Norihisa Komoda

Proceedings of the ICE-B 2007, 2007

2000

Metadata representation in XML for Internet-based electronic XML application from business to government.

Makoto Imamura, Ryuuji Nagahama, Katsushi Suzuki, Akehiro Watabe, Hidekazu Tsuji

Proceedings of the Seventh International Conference on Parallel and Distributed Systems Workshops, 2000

1999

Sharing SGML/XML Document Information Conformable to Business Standards.

Makoto Imamura, Osamu Moriguchi, Katsushi Suzuki, Hidekazu Tsuji

Proceedings of the 1999 International Conference on Parallel Processing Workshops, 1999