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Mining frequent patterns in transaction databases, time-series databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still costly, especially when there exist prolific patterns and/or(More)
Mining frequent patterns in transaction databases, time-series databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still costly, especially when there exist a large number of(More)
Partial periodicity search, i.e., search for partial periodic patterns in time-series databases, is an interesting data mining problem. Previous studies on periodicity search mainly consider finding full periodic patterns, where every point in time contributes (precisely or approximately) to the periodicity. However, partial periodicity is very common in(More)
Jiawei Han Wan Gong Yiwen Yin Intelligent Database Systems Research Laboratory, School of Computing Science Simon Fraser University, Burnaby, BC, Canada V5A 1S6 E-mail: fhan, wgong, yiwenyg@cs.sfu.ca Abstract Periodicity search, that is, search for cyclicity in time-related databases, is an interesting data mining problem. Most previous studies have been on(More)
Partial periodicity search, i.e., search for partial periodic patterns in time-series databases, is an interesting data mining problem. Previous studies on periodicity search mainly consider finding full periodic patterns, where every point in time contributes (precisely or approximately) to the periodicity. However, partial periodicity is very common in(More)
Positive and negative sequential patterns mining is used to discover interesting sequential patterns in a incremental transaction databases, and it is one of the essential data mining tasks widely used in various application fields. Implementation of this approach, construct tree for appended transactions (new upcoming data) and will merge this tree with(More)
The Internet has impacted almost every aspect of our society. Since the number of web sites and web pages has grown rapidly, discovering and understanding web users’ surfing behavior are essential for the development of successful web monitoring and recommendation systems. To capture users’ web access behavior, one promising approach is web usage mining(More)
The problem of mining high quality frequent substructures from a large collection of semi-structured data has recently attracted a lot of research. There are various efficient algorithms available for discovering frequent substructures in a large structured data, where both of the patterns and the data are modeled by labeled unordered trees. In this paper,(More)
Our capabilities of both generating and collecting data have been increasing rapidly in the last several decades. Contributing factors include the widespread use of bar codes for most commercial products, the computerization of many business, scienti c and government transactions and managements, and advances in data collection tools ranging from scanned(More)
Road accident is one of the crucial areas of research in India. A variety of research has been done on data collected through police records covering a limited portion of highways. The analysis of such data can only reveal information regarding that portion only; but accidents are scattered not only on highways but also on local roads. A different source of(More)