NDLI: Indexation based on the textual evolution

Content Provider	IEEE Xplore Digital Library
Author	Marteau, H. Vincent, N.
Copyright Year	2005
Description	Author affiliation: Lab. d'Informatique, Univ. Francois-Rabelais de Tours, France (Marteau, H.)
Abstract	In this work, we have studied different methods that try to bring out the notion of textual evolution. The primary objective of these methods is to bring additional information figuring the logical process adopted during the text creation. The first method presented in this paper relies on an automaton for creating images. It also describes the rules of the machine and chosen evaluation measures. The second method is based on statistical techniques. The fusion of these two methods results in a nonsupervised classification method to achieve better results on different corpuses.
Sponsorship	IEEE Syst., Man and Cybernetics Tech. Comm. on Cybernetics, Hong Kong Polytechnic Univ. Hebei Univ. South China Univ. Chongqing Univ. Sun Yat-sen Univ. Harbin Inst. of Technol. and Int. Univ. in Germany
Starting Page	1583
Ending Page	1588
File Size	329532
Page Count	6
File Format	PDF
ISBN	0780390911
DOI	10.1109/ICMLC.2005.1527197
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-08-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Humans Evolution (biology) Learning automata Frequency Data analysis Psychology Neural networks Thermodynamics DNA Information retrieval evolution Text indexation structure of text
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

Motion Retrieval Based on Multiple Instance Learning by Isomap and RBF

Knowledge discovery from text documents based on paragraph maps

Statistical learning for effective visual information retrieval

A Neural Network Approach for Bridging the Semantic Gap in Texture Image Retrieval

What can XML do for textual information retrieval on the WEB?

Textual information retrieval : An approach based on language modeling and neural networks

Supervised learning of regular languages by neural networks

Information retrieval model based on neural networks using neighborhood

An adaptive wireless push system for high-speed data broadcasting

Indexation based on the textual evolution

Similar Documents

Motion Retrieval Based on Multiple Instance Learning by Isomap and RBF

Knowledge discovery from text documents based on paragraph maps

Statistical learning for effective visual information retrieval

A Neural Network Approach for Bridging the Semantic Gap in Texture Image Retrieval

What can XML do for textual information retrieval on the WEB?

Textual information retrieval : An approach based on language modeling and neural networks

Supervised learning of regular languages by neural networks

Information retrieval model based on neural networks using neighborhood

An adaptive wireless push system for high-speed data broadcasting

Indexation based on the textual evolution