Iranian Journal of Information Processing and Management

Iranian Journal of Information Processing and Management

Automatic Detection of the Boundary between Metadata and Body in Persian Theses using BA_SVM

Authors
Mohadese Rahnama
Seyed Mohammad Hossein Hasheminejad
Jalal A Nasiri
10.52547/jipm.36.4.1159
Abstract
Metadata extraction facilitates the process of indexing and improves information retrieval. Also automation of this process increases efficiency more than manual extraction. The example of the thesis metadata are names of students, professors, title, field, degree, abstract, keywords, etc. In this paper the aim is automatic boundary detection of metadata from the main body in Persian theses. Therefore, 250 theses collected from IRANDOC system. Features were extracted from paragraphs of each thesis then paragraphs were classified using support vector machine into 2 classes: metadata and body. In this study, Bat algorithm is used to set the parameter of SVM. The result reveals that the proposed method predicts type of paragraphs with 96.6 percent accuracy.
Keywords
Metadata Extraction
Information Extraction
Support Vector Machine (SVM)
Metaheuristic algorithm
Bat Algorithm (BA)
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Iranian Journal of Information Processing and Management
Volume 36, Issue 4 - Serial Number 106
Summer 2021
Pages 1159-1179

  • Receive Date 10 December 2022