NDLI: Automated text document categorization

Content Provider	IEEE Xplore Digital Library
Author	Yasotha, R. Charles, E.Y.A.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci., Univ. of Jaffna, Jaffna, Sri Lanka (Charles, E.Y.A.) \|\| Dept. of Phys. Sci., Univ. of Jaffna, Jaffna, Sri Lanka (Yasotha, R.)
Abstract	During the last two decades the number of text documents in digital form has grown enormously. It is necessary to categorize documents into topics and sub topics for easy retrieval. Manual categorization of text documents can be done only by experts and it is a time consuming task. As a consequence, it is of great practical importance to be able to automatically organize and classify documents. There are two approaches, rule-based and machine learning-based, that are used to automate classification task. Both have some limitations. Rules may conflict each other and have to be reconstructed when a target domain changes, are such two limitations in the rule based approaches. Machine learning approaches require proper training data and they do not accountable with the classification results. Motivated by such limitations, this paper proposes a Latent Dirichlet Allocation (LDA) based approach to automatically classify text documents. In order to develop and test the proposed approach on a realistic set up, ACM (Association for Computing Machinery) Computing Classification System (CCS) is selected as the target platform and 9100 computer science related articles categorized under ACM-CCS were selected. The experimental results show that the proposed approach is effective for classifying text documents and is applicable to a domain with large number of categories in multiple levels.
Starting Page	522
Ending Page	528
File Size	1284227
Page Count	7
File Format	PDF
ISBN	9781509019496
e-ISBN	9781509019502
DOI	10.1109/IntelCIS.2015.7397271
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-12-12
Publisher Place	Egypt
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Latent Dirichlet Allocation Smoothing methods Computational modeling Text categorization Document classification Artificial neural networks LDA Hardware ACM ACM-CCS
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
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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

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