Paper Info
Title
Discovery of events with negative behavior against given sequential patterns
Abstract
The dramatic drop in the prices of data collection and storage devices has not only enabled organisations to store almost every activity of their business processes, they can also retain every state of these activities as well. Availability of these masses of data also means that by implementing different data mining techniques we can yield more accurate and useful information to be used for important decision making. One of the key mining techniques on such data is to discover sequential patterns. Most of the existing sequential pattern mining approaches mainly deal with finding the positive behaviour of a sequential pattern that can help in predicting the next event after a sequence of events. In this paper we propose the concept of Negative Behaviour Against the Sequential Pattern (NBASP) that is to discover the events/event-sets which are unlikely to follow the given sequential pattern and discuss its applications in a variety of domains. A comprehensive problem definition and efficient algorithm to discover NBASP is presented.
Year
DOI
Venue
2010
10.1109/IS.2010.5548370
IEEE Conf. of Intelligent Systems
Keywords
Field
DocType
data mining,storage management,data collection,data mining technique,negative behavior,sequential pattern discovery,storage device,component,data mining,post mining environment,sequential pattern
Data collection,Data structure,Data mining,Business process,Computer science,Decision support system,Medical treatment,Artificial intelligence,Storage management,Sequential Pattern Mining,Machine learning
Conference
ISBN
Citations 
PageRank 
978-1-4244-5164-7
3
0.38
References 
Authors
3
4
Name
Order
Citations
PageRank
Fahad Anwar1172.03
Ilias Petrounias220037.52
Tim Morris371.79
Vassilis S. Kodogiannis427235.17