Makoto Imamura

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

Eamonn J. Keogh, Takaaki Nakamura, Makoto Imamura, 2020, 2020 IEEE International Conference on Data Mining (ICDM).

Anomaly Detection in Real-Valued Multidimensional Time Series

Daniel Nikovski, Makoto Imamura, Takahisa Hirata, 2014 .

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

Masaru Kitsuregawa, Nobuhiro Kaji, Masashi Toyoda, 2009, ACL.

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

Eamonn J. Keogh, Yan Zhu, Eamonn Keogh, 2018, Knowledge and Information Systems.

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

Eamonn J. Keogh, Yan Zhu, Daniel Nikovski, 2018, IJCAI.

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

Eamonn J. Keogh, D. Nikovski, Yan Zhu, 2018, Knowledge and Information Systems.

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

Eamonn J. Keogh, Yan Zhu, Daniel Nikovski, 2017, 2017 IEEE International Conference on Data Mining (ICDM).

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

Michael Jones, D. Nikovski, Makoto Imamura, 2016, Data Mining and Knowledge Discovery.

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

Eamonn J. Keogh, Eamonn Keogh, Takaaki Nakamura, 2020, KDD.

A Guidance Generation Method Based on Joint Vector Model for an Exercise Training Support System

Junji Tsuda, Makoto Imamura, Yuhei Yamaguchi, 2020 .

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

Eamonn J. Keogh, Takaaki Nakamura, Makoto Imamura, 2023, Data Mining and Knowledge Discovery.

Invited Paper: An Anomaly Detection System for Equipment Condition Monitoring

Michael Jones, D. Nikovski, Makoto Imamura, 2017 .

An Anomaly Detection Method with Exemplar Subsequence for Time Series Data

Takaaki Nakamura, Makoto Imamura, Masashi Tatedoko, 2016 .

Time Series Data Query Language TPQL for Anomaly Detection in Facility

Shinji Kitagami, Tatsuji Munaka, Makoto Imamura, 2014 .

Sharing SGML/XML document information conformable to business standards

Hidekazu Tsuji, Osamu Moriguchi, Makoto Imamura, 1999, Proceedings of the 1999 ICPP Workshops on Collaboration and Mobile Computing (CMC'99). Group Communications (IWGC). Internet '99 (IWI'99). Industrial Applications on Network Computing (INDAP). Multime.