NDLI: Integrated genetic - fuzzy approach for items with single minimum support using 3-dimensional k-means clustering

Content Provider	IEEE Xplore Digital Library
Author	Fatma, S.N. Bakal, J.W.
Copyright Year	2012
Description	Author affiliation: Department of Information Technology, Mumbai University, India (Bakal, J.W.) \|\| Department of Computer, Mumbai University, Pillai's Institute of Information Technology, New Panvel, India (Fatma, S.N.)
Abstract	Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. Most conventional data-mining algorithms identify the relationships among transactions using binary values. Transactions with quantitative values are however commonly seen in real-world applications. The fuzzy concepts are used to represent item importance, item quantities, minimum supports and minimum confidences. Each attribute uses only the linguistic term with the maximum cardinality in the mining process. The number of items is thus the same as that of the original attributes, making the processing time reduced. It uses a combination of large 1-itemsets and membership-function suitability to evaluate the fitness values of chromosomes. The calculation for large 1-itemsets could take a lot of time, especially when the database to be scanned could not totally fed into main memory. In this system, an enhanced approach, called the cluster-based fuzzy-genetic mining algorithm. It divides the chromosomes in a population into clusters by the 3-dimensional k-means clustering approach and evaluates each individual according to both cluster and their own information. A genetic-fuzzy data-mining algorithm for extracting fit membership functions and multilevel association rules with its confidence from quantitative transactions is shown
Starting Page	435
Ending Page	442
File Size	1399651
Page Count	8
File Format	PDF
ISBN	9781467351140
e-ISBN	9781467351164
DOI	10.1109/HIS.2012.6421374
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-04
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genetic algorithm(GA) fuzzy set Clustering algorithms data mining chromosomes confidence 3 dimensional k-means Clustering membership functions Quantitative transactions Fuzzy Association Rules Biological cells
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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