Mining Hierarchical Time‐interval Sequential Patterns in Sequence Databases

• Main Authors: Chieh-I Yang, 楊杰翊
• Other Authors: Fan Wu
• Format: Others
• Language: en_US
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/49035383302851164192

碩士 === 國立中正大學 === 資訊管理所暨醫療資訊管理所 === 98 === Mining sequential patterns is an important issue in data mining and has many applications. An extended work of sequential pattern mining, called hierarchical 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 hierarchical time-interval sequential patterns and then presents a novel algorithm, named HTI-PrefixSpan, for discovering the complete set of hierarchical time-interval sequential patterns. Experimental results show that the proposed algorithm is not only effective on the test dataset but also could discover patterns with cross level time-interval.