NDLI: Keyword extraction using backpropagation neural networks and rule extraction

Content Provider	IEEE Xplore Digital Library
Author	Azcarraga, A. Liu, M.D. Setiono, R.
Copyright Year	2012
Description	Author affiliation: School of Computing, National University of Singapore, Computing 1, 13 Computing Drive, Singapore 117417 (Setiono, R.) \|\| College of Computer Studies, De La Salle University, 2401 Taft Avenue, Manila 1004. Philippines (Azcarraga, A.; Liu, M.D.)
Abstract	Keyword extraction is vital for Knowledge Management System, Information Retrieval System, and Digital Libraries as well as for general browsing of the web. Keywords are often the basis of document processing methods such as clustering and retrieval since processing all the words in the document can be slow. Common models for automating the process of keyword extraction are usually done by using several statistics-based methods such as Bayesian, K-Nearest Neighbor, and Expectation-Maximization. These models are limited by word-related features that can be used since adding more features will make the models more complex and difficult to comprehend. In this research, a Neural Network, specifically a backpropagation network, will be used in generalizing the relationship of the title and the content of articles in the archive by following word features other than TF-IDF, such as position of word in the sentence, paragraph, or in the entire document, and formats such as heading, and other attributes defined beforehand. In order to explain how the backpropagation network works, a rule extraction method will be used to extract symbolic data from the resulting backpropagation network. The rules extracted can then be transformed into decision trees performing almost as accurate as the network plus the benefit of being in an easily comprehensible format.
Starting Page	1
Ending Page	7
File Size	812639
Page Count	7
File Format	PDF
ISBN	9781467314886
ISSN	21614393
e-ISBN	9781467314909
e-ISBN	9781467314893
DOI	10.1109/IJCNN.2012.6252618
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-10
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Feature extraction Neural networks Data mining Training Backpropagation Accuracy Abstracts document analysis rule extraction keyword extraction
Content Type	Text
Resource Type	Article

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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
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