NDLI: Efficient mining of understandable patterns from multivariate interval time series

Content Provider	Springer Nature Link
Author	Mörchen, Fabian Ultsch, Alfred
Copyright Year	2007
Abstract	We present a new method for the understandable description of local temporal relationships in multivariate data, called Time Series Knowledge Mining (TSKM). We define the Time Series Knowledge Representation (TSKR) as a new language for expressing temporal knowledge in time interval data. The patterns have a hierarchical structure, with levels corresponding to the temporal concepts duration, coincidence, and partial order. The patterns are very compact, but offer details for each element on demand. In comparison with related approaches, the TSKR is shown to have advantages in robustness, expressivity, and comprehensibility. The search for coincidence and partial order in interval data can be formulated as instances of the well known frequent itemset problem. Efficient algorithms for the discovery of the patterns are adapted accordingly. A novel form of search space pruning effectively reduces the size of the mining result to ease interpretation and speed up the algorithms. Human interaction is used during the mining to analyze and validate partial results as early as possible and guide further processing steps. The efficacy of the methods is demonstrated using two real life data sets. In an application to sports medicine the results were recognized as valid and useful by an expert of the field.
Starting Page	181
Ending Page	215
Page Count	35
File Format	PDF
ISSN	13845810
Journal	Data Mining and Knowledge Discovery
Volume Number	15
Issue Number	2
e-ISSN	1573756X
Language	English
Publisher	Springer US
Publisher Date	2007-04-21
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Knowledge discovery Time series Interval patterns Allen’s relations Information Storage and Retrieval Statistics for Engineering, Physics, Computer Science, Chemistry & Geosciences Statistics Artificial Intelligence (incl. Robotics) Computing Methodologies Data Mining and Knowledge Discovery
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Information Systems 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
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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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