NDLI: Application of SVM in Citation Information Extraction

Content Provider	IEEE Xplore Digital Library
Author	Jiguang Liang Layton, R. Wei Wang
Copyright Year	2011
Abstract	Support Vector Machines are an effective form of binary-class classification algorithm. To enhance the utilization of text structural features for information extraction, which are greatly restricted by the Hidden Markov Model (HMM), this paper proposes a support vector machine multi-class classification based on Markov properties to extract the information from a citation database. The proposed model extracts symbol characteristics as features and composes a binary tree of the transition probabilities. Experiments show that the proposed method outperforms HMM and basic SVM methods.
Starting Page	33
Ending Page	35
File Size	227230
Page Count	3
File Format	PDF
ISBN	9781457720079
DOI	10.1109/IWCDM.2011.15
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Support Vector Machine (SVM) Hidden Markov models Binary trees Classification Markov processes Probability Feature extraction Symbol feature Data mining
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
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Application of SVM in Citation Information Extraction