MuTIny: A Multi-Time Interval Pattern Discovery Approach To Preserve The Temporal Information In Between

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Abstract
Finding trends, patterns, and relationships among patterns are very relevant tasks when dealing with time-oriented data and information. However, most of the proposed methods have a sequence of events as outcome, lacking either any knowledge about the intervals between them or about after how much time a particular pattern will reoccur. We present MuTIny, a novel approach extending the I-Apriori algorithm, which is able to discover so called multi-time interval patterns and we describe how it can be customized according to users’ needs. Moreover, a real world example illustrates its usefulness.
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Author Address
Year of Publication
2010
Conference Name
IADIS European Conference on Data Mining (ECDM 2010)
Number of Pages
Date Published
July
Type of Work
Publisher
International Association for Development of the Information Society
Conference Location
Freiburg, Germany
ISBN Number
978-972-8939-23-6
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URL
http://publik.tuwien.ac.at/files/PubDat_218035.pdf
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