NDLI: Generative model-based document clustering: a comparative study

Content Provider	Springer Nature Link
Author	Zhong, Shi Ghosh, Joydeep
Copyright Year	2005
Abstract	This paper presents a detailed empirical study of 12 generative approaches to text clustering, obtained by applying four types of document-to-cluster assignment strategies (hard, stochastic, soft and deterministic annealing (DA) based assignments) to each of three base models, namely mixtures of multivariate Bernoulli, multinomial, and von Mises-Fisher (vMF) distributions. A large variety of text collections, both with and without feature selection, are used for the study, which yields several insights, including (a) showing situations wherein the vMF-centric approaches, which are based on directional statistics, fare better than multinomial model-based methods, and (b) quantifying the trade-off between increased performance of the soft and DA assignments and their increased computational demands. We also compare all the model-based algorithms with two state-of-the-art discriminative approaches to document clustering based, respectively, on graph partitioning (CLUTO) and a spectral coclustering method. Overall, DA and CLUTO perform the best but are also the most computationally expensive. The vMF models provide good performance at low cost while the spectral coclustering algorithm fares worse than vMF-based methods for a majority of the datasets.
Starting Page	374
Ending Page	384
Page Count	11
File Format	PDF
ISSN	02191377
Journal	Knowledge and Information Systems
Volume Number	8
Issue Number	3
e-ISSN	02193116
Language	English
Publisher	Springer-Verlag
Publisher Date	2005-02-10
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Comparative study Document clustering Model-based clustering Business Information Systems Information Systems and Communication Service
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Information Systems Human-Computer Interaction Hardware and Architecture Software

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

Correlation-Based Web Document Clustering for Adaptive Web Interface Design

Multi-step density-based clustering

MDL-based time series clustering

Interpretable and reconfigurable clustering of document datasets by deriving word-based rules

Text document clustering using global term context vectors

Statistical semantics for enhancing document clustering

Clustering XML documents by patterns

Query directed clustering

Overlapping correlation clustering

Generative model-based document clustering: a comparative study

Similar Documents

Correlation-Based Web Document Clustering for Adaptive Web Interface Design

Multi-step density-based clustering

MDL-based time series clustering

Interpretable and reconfigurable clustering of document datasets by deriving word-based rules

Text document clustering using global term context vectors

Statistical semantics for enhancing document clustering

Clustering XML documents by patterns

Query directed clustering

Overlapping correlation clustering

Generative model-based document clustering: a comparative study