NDLI: Proportional fault-tolerant data mining with applications to bioinformatics

Content Provider	Springer Nature Link
Author	Lee, Guanling Peng, Sheng Lung Lin, Yuh Tzu
Copyright Year	2009
Abstract	The mining of frequent patterns in databases has been studied for several years, but few reports have discussed for fault-tolerant (FT) pattern mining. FT data mining is more suitable for extracting interesting information from real-world data that may be polluted by noise. In particular, the increasing amount of today’s biological databases requires such a data mining technique to mine important data, e.g., motifs. In this paper, we propose the concept of proportional FT mining of frequent patterns. The number of tolerable faults in a proportional FT pattern is proportional to the length of the pattern. Two algorithms are designed for solving this problem. The first algorithm, named FT-BottomUp, applies an FT-Apriori heuristic and finds all FT patterns with any number of faults. The second algorithm, FT-LevelWise, divides all FT patterns into several groups according to the number of tolerable faults, and mines the content patterns of each group in turn. By applying our algorithm on real data, two reported epitopes of spike proteins of SARS-CoV can be found in our resulting itemset and the proportional FT data mining is better than the fixed FT data mining for this application.
Starting Page	461
Ending Page	469
Page Count	9
File Format	PDF
ISSN	13873326
Journal	Information Systems Frontiers
Volume Number	11
Issue Number	4
e-ISSN	15729419
Language	English
Publisher	Springer US
Publisher Date	2009-02-19
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Bioinformatics FT support Fault-tolerant frequent pattern Data mining Operations Research/Decision Theory Systems Theory, Control Management of Computing and Information Systems Business Information Systems
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Computer Networks and Communications Information Systems Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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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