NDLI: Finding approximate frequent patterns in streaming medical data

Content Provider	IEEE Xplore Digital Library
Author	Lin, J. Yuan Li
Copyright Year	2010
Description	Author affiliation: Computer Science Department, George Mason University, Fairfax, VA (Lin, J.; Yuan Li)
Abstract	Time series data is ubiquitous and plays an important role in virtually every domain. For example, in medicine, the advancement of computer technology has enabled more sophisticated patients monitoring, either on-site or remotely. Such monitoring produces massive amount of time series data, which contain valuable information for pattern learning and knowledge discovery. In this paper, we explore the problem of identifying frequently occurring patterns, or motifs, in streaming medical data. The problem of frequent patterns mining has many potential applications, including compression, summarization, and event prediction. We propose a novel approach based on grammar induction that allows the discovery of approximate, variable-length motifs in streaming data. The preliminary results show that the grammar-based approach is able to find some important motifs in some medical data, and suggest that using grammar-based algorithms for time series pattern discovery might be worth exploring.
Starting Page	13
Ending Page	18
File Size	1006921
Page Count	6
File Format	PDF
ISBN	9781424491674
ISSN	10637125
e-ISBN	9781424491681
DOI	10.1109/CBMS.2010.6042675
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-12
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Time series analysis Grammar Approximation algorithms Algorithm design and analysis Data mining Probabilistic logic Compression algorithms Grammar Induction Time Series Frequent Patterns
Content Type	Text
Resource Type	Article
Subject	Radiology, Nuclear Medicine and Imaging Computer Science Applications

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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