NDLI: Bayesian multidimensional scale clustering based on Dirichlet process

Content Provider	IEEE Xplore Digital Library
Author	Qing Xiangyun Wang Xingyu
Copyright Year	2008
Description	Author affiliation: Coll. of Inf. Sci. & Technol., East China Univ. of Sci. & Technol., Shanghai (Qing Xiangyun; Wang Xingyu)
Abstract	An important reason for doing multidimensional scaling is to cluster the objects which are only given dissimilarity metrics. A prior number of components could be infinite in a Bayesian mixture model. In this work we apply infinite Gaussian mixture model and present a Bayesian multidimensional scale clustering method based on Dirichlet process. Estimating the parameters of Bayesian multidimensional scaling model is done using Markov chain Monte Carlo. As the method avoids the model selection, it can be used not only for generating low-dimensional coordinates and model-based clustering simultaneously, but also for choosing the number of clusters and performing parameters of components at the same time.
Starting Page	546
Ending Page	550
File Size	371101
Page Count	5
File Format	PDF
ISBN	9787900719706
DOI	10.1109/CHICC.2008.4605443
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute Of Intelligence M&C Technical Of KMUST
Subject Keyword	Cluster analysis Microwave integrated circuits Information science Analytical models Monte Carlo methods Bayesian methods Clustering methods Infinite mixture model Markov chain Monte Carlo Dirichlet process Electronic mail Multidimensional scaling
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	Mr. Siddhartha Mukherjee siddhartha@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	ndl-support@iitkgp.ac.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Libarray 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

Choice of Dimension Using Reversible Jump Markov Chain Monte Carlo in the Multidimensional Scaling

Model-Based Clustering With Dissimilarities : A Bayesian Approach

Music Analysis Using Hidden Markov Mixture Models

A Split-Merge Markov Chain Monte Carlo Procedure for the Dirichlet Process Mixture Model (2000)

Variational inference for dirichlet process mixtures (2006).

Confronting Prior Convictions: On Issues of Prior Sensitivity and Likelihood Robustness in Bayesian Analysis

Bayesian semiparametric stochastic volatility modeling

Bayesian inference for dynamic models with Dirichlet process mixtures (2006)

Bayesian Inference for Dynamic Models with Dirichlet Process Mixtures

Bayesian multidimensional scale clustering based on Dirichlet process

Similar Documents

Choice of Dimension Using Reversible Jump Markov Chain Monte Carlo in the Multidimensional Scaling

Model-Based Clustering With Dissimilarities : A Bayesian Approach

Music Analysis Using Hidden Markov Mixture Models

A Split-Merge Markov Chain Monte Carlo Procedure for the Dirichlet Process Mixture Model (2000)

Variational inference for dirichlet process mixtures (2006).

Confronting Prior Convictions: On Issues of Prior Sensitivity and Likelihood Robustness in Bayesian Analysis

Bayesian semiparametric stochastic volatility modeling

Bayesian inference for dynamic models with Dirichlet process mixtures (2006)

Bayesian Inference for Dynamic Models with Dirichlet Process Mixtures

Bayesian multidimensional scale clustering based on Dirichlet process