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Title:
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MuTIny: A MULTI-TIME INTERVAL PATTERN DISCOVERY APPROACH TO PRESERVE THE TEMPORAL INFORMATION IN BETWEEN |
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Author(s):
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Alessio Bertone, Tim Lammarsch, Thomas Turic, Wolfgang Aigner, Silvia Miksch, Johannes Gärtner |
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ISBN:
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978-972-8939-23-6 |
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Editors:
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António Palma dos Reis and Ajith P. Abraham |
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Year:
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2010 |
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Edition:
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Single |
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Keywords:
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Temporal Data Mining, Interval Mining, Pattern Finding, Time-oriented Data |
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Type:
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Short Paper |
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First Page:
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101 |
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Last Page:
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108 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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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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