@inproceedings{eaa3bd3006c5488c903d1ee7d0348d8a,
title = "Mining multi-level time-interval sequential patterns in sequence databases",
abstract = "Mining sequential patterns is an important issue in data mining and has many applications. An extended work of sequential pattern mining, called time-interval sequential pattern mining, is proposed to retrieve time-interval information between successive items. However, previous work only considers single-level time-interval in pattern extraction, which means sequential patterns with cross-level time-intervals are completely ignored. Therefore, this study first defines multi-level time-interval sequential patterns and then presents a novel algorithm, named MLTI-PrefixSpan, for discovering the complete set of multi-level time-interval sequential patterns. Experimental results show that the proposed algorithm is effective on the test dataset.",
keywords = "Data mining, Sequential patterns, Time-interval",
author = "Hu, {Ya Han} and Fan Wu and Yang, {Chieh I.}",
year = "2010",
language = "???core.languages.en_GB???",
isbn = "9788988678213",
series = "2nd International Conference on Software Engineering and Data Mining, SEDM 2010",
pages = "416--421",
booktitle = "2nd International Conference on Software Engineering and Data Mining, SEDM 2010",
note = "null ; Conference date: 23-06-2010 Through 25-06-2010",
}