DocumentCode
467708
Title
Mining Negative Sequential Patterns in Transaction Databases
Author
Ouyang, Wei-min ; Huang, Qin-hua
Author_Institution
Shanghai Univ. of Sport, Shanghai
Volume
2
fYear
2007
fDate
19-22 Aug. 2007
Firstpage
830
Lastpage
834
Abstract
Sequential pattern is an important research topic in data mining and knowledge discovery. Sequential pattern is traditionally formed as (A, B) where A and B are frequent sequence in a transaction database. We extend this definition to include sequential patterns of forms (A, notB), (notA, B) and (notA, notB), which present negative sequential patterns among sequences. We call patterns of the form (A, B) positive sequential patterns, and patterns of the other forms negative patterns. Negative sequential patterns can also provide very useful insight view into the data set although they are different from positive ones. We put forward a discovery algorithm for mining negative sequential patterns from large transaction database in this paper.
Keywords
data mining; data mining; frequent sequence; negative sequential patterns; transaction databases; Association rules; Conference management; Cybernetics; Data engineering; Data mining; Engineering management; Itemsets; Knowledge management; Machine learning; Transaction databases; Frequent sequence; Infrequent sequence; Negative sequential patterns; Sequential patterns;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-0973-0
Electronic_ISBN
978-1-4244-0973-0
Type
conf
DOI
10.1109/ICMLC.2007.4370257
Filename
4370257
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