NDLI: PAID: Mining Sequential Patterns by Passed Item Deduction in Large Databases

Content Provider	IEEE Xplore Digital Library
Author	Zhenglu Yang Kitsuregawa, M. Yitong Wang
Copyright Year	2006
Description	Author affiliation: Dept. of Inf. & Commun. Eng., Tokyo Univ. (Zhenglu Yang; Kitsuregawa, M.)
Abstract	Sequential pattern mining is very important because it is the basis of many applications. Yet how to efficiently implement the mining is difficult due to the inherent characteristic of the problem - the large size of the dataset. Although there has been a great deal of effort on sequential pattern mining in recent years, its performance is still far from satisfactory. In this paper, we have proposed a new algorithm called passed item deduced sequential pattern mining (abbreviated as PAID), which can efficiently get all the frequent sequential patterns from a large database. The main difference between our strategy and the existing works is that other algorithms accumulate the candidate support in each iteration from scratch, in contrast, PAID makes good use of the temporary results (support value) of k-length frequent patterns on discovering (k+1)-length patterns, which can reduce the search space greatly in mining sequential patterns. Our experimental results and performance studies show that PAID outperforms the previous works by meaningful margins on large datasets
Sponsorship	IEEE Comput. Soc. IEEE Concordia Univ
Starting Page	113
Ending Page	120
File Size	329052
Page Count	8
File Format	PDF
ISBN	0769525776
ISSN	10988068
DOI	10.1109/IDEAS.2006.34
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-12-11
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Deductive databases Data mining Itemsets Association rules Computer science Time factors Surges Application software Pattern analysis Biology
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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