NDLI: Clustering ICT Indicators of Bhutan using Two Level HSOM Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Tshering Arch-int, S.
Copyright Year	2008
Description	Author affiliation: Khon Kaen Univ., Khon Kaen (Tshering)
Abstract	In this paper, a novel two level HSOM algorithm for clustering information and communication technology (ICT) indicators is presented. The purpose of this research study is to analyze the twenty districts ICT data of Bhutan using HSOM clustering algorithm. The HSOM possesses a two-level hybrid connectionist architecture that comprises (i) an agglomerative hierarchical clustering algorithm to create hierarchy of data in dendrogram from the principal component analysis(PCA) reduced data and (ii) an unsupervised neural network based Self-Organizing map classifier,which generates the final cluster output in single umatrix map. It is confirmed that HSOM obtains the effective output reflecting distribution state of input data. Ultimately we analyzed present scenario of ICT situation with clustering algorithm. ICT is one of the enabler of socio-economic developmental activities in Bhutan. Outcome from this research will help newly elected democratic government to achieve sustain able and equitable development in its $10^{th}$ five year plan (2008-2013).
Starting Page	121
Ending Page	127
File Size	428558
Page Count	7
File Format	PDF
ISBN	9780769532639
DOI	10.1109/SNPD.2008.22
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-08-06
Publisher Place	Thailand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis SOM Neurons Clustering algorithms Computer architecture HSOM Distance measurement Covariance matrix Clustering Principal component analysis PCA
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

RPCL-based local PCA algorithm

FEMA: A Fast Expectation Maximization Algorithm based on Grid and PCA

Recognition of partial discharge patterns

Isotropic PCA and Affine-Invariant Clustering

Distributed PCA-based anomaly detection in telephone networks through legitimate-user profiling

Improved Spectral Clustering Using Adaptive Mahalanobis Distance

Incremental PCA-LDA algorithm

Performance improvement for face recognition using PCA and two-dimensional PCA

On principal component analysis for data with tolerance

Clustering ICT Indicators of Bhutan using Two Level HSOM Algorithm

Similar Documents

RPCL-based local PCA algorithm

FEMA: A Fast Expectation Maximization Algorithm based on Grid and PCA

Recognition of partial discharge patterns

Isotropic PCA and Affine-Invariant Clustering

Distributed PCA-based anomaly detection in telephone networks through legitimate-user profiling

Improved Spectral Clustering Using Adaptive Mahalanobis Distance

Incremental PCA-LDA algorithm

Performance improvement for face recognition using PCA and two-dimensional PCA

On principal component analysis for data with tolerance

Clustering ICT Indicators of Bhutan using Two Level HSOM Algorithm