1. Automatic Recognition of Learning Resource Category in a Digital Library
- Author
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Banerjee, Soumya, Sanyal, Debarshi Kumar, Chattopadhyay, Samiran, Bhowmick, Plaban Kumar, and Das, Partha Pratim
- Subjects
Computer Science - Digital Libraries ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Digital libraries often face the challenge of processing a large volume of diverse document types. The manual collection and tagging of metadata can be a time-consuming and error-prone task. To address this, we aim to develop an automatic metadata extractor for digital libraries. In this work, we introduce the Heterogeneous Learning Resources (HLR) dataset designed for document image classification. The approach involves decomposing individual learning resources into constituent document images (sheets). These images are then processed through an OCR tool to extract textual representation. State-of-the-art classifiers are employed to classify both the document image and its textual content. Subsequently, the labels of the constituent document images are utilized to predict the label of the overall document., Comment: 2 pages, 3 figures, Published in JCDL 21
- Published
- 2023
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