Duration and Interval Hidden Markov Model for sequential data analysis

Hiromi Narimatsu; Hiroyuki Kasai

doi:10.1109/IJCNN.2015.7280808

Duration and Interval Hidden Markov Model for sequential data analysis

Hiromi Narimatsu, Hiroyuki Kasai

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Citations (Scopus)

Abstract

Analysis of sequential event data has been recognized as one of the essential tools in data modeling and analysis field. In this paper, after the examination of its technical requirements and issues to model complex but practical situation, we propose a new sequential data model, dubbed Duration and Interval Hidden Markov Model (DI-HMM), that efficiently represents 'state duration' and 'state interval' of data events. This has significant implications to play an important role in representing practical time-series sequential data. This eventually provides an efficient and flexible sequential data retrieval. Numerical experiments on synthetic and real data demonstrate the efficiency and accuracy of the proposed DI-HMM.

Original language	English
Title of host publication	2015 International Joint Conference on Neural Networks, IJCNN 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479919604, 9781479919604, 9781479919604, 9781479919604
DOIs	https://doi.org/10.1109/IJCNN.2015.7280808
Publication status	Published - 2015 Sept 28
Externally published	Yes
Event	International Joint Conference on Neural Networks, IJCNN 2015 - Killarney, Ireland Duration: 2015 Jul 12 → 2015 Jul 17

Publication series

Name	Proceedings of the International Joint Conference on Neural Networks
Volume	2015-September

Other

Other	International Joint Conference on Neural Networks, IJCNN 2015
Country/Territory	Ireland
City	Killarney
Period	15/7/12 → 15/7/17

Keywords

HMM
HSMM
Sequential data analysis
State duration
State interval

ASJC Scopus subject areas

Software
Artificial Intelligence

Access to Document

10.1109/IJCNN.2015.7280808

Cite this

Narimatsu, H., & Kasai, H. (2015). Duration and Interval Hidden Markov Model for sequential data analysis. In 2015 International Joint Conference on Neural Networks, IJCNN 2015 Article 7280808 (Proceedings of the International Joint Conference on Neural Networks; Vol. 2015-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.2015.7280808

Duration and Interval Hidden Markov Model for sequential data analysis. / Narimatsu, Hiromi; Kasai, Hiroyuki.
2015 International Joint Conference on Neural Networks, IJCNN 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7280808 (Proceedings of the International Joint Conference on Neural Networks; Vol. 2015-September).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Narimatsu, H & Kasai, H 2015, Duration and Interval Hidden Markov Model for sequential data analysis. in 2015 International Joint Conference on Neural Networks, IJCNN 2015., 7280808, Proceedings of the International Joint Conference on Neural Networks, vol. 2015-September, Institute of Electrical and Electronics Engineers Inc., International Joint Conference on Neural Networks, IJCNN 2015, Killarney, Ireland, 15/7/12. https://doi.org/10.1109/IJCNN.2015.7280808

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Duration and Interval Hidden Markov Model for sequential data analysis

Abstract

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Keywords

ASJC Scopus subject areas

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