- Title
- Information extraction model from Ge’ez texts
- Creator
- Gebeyehu, Seffi, Wolde, Worke, Shibeshi, Zelalem S
- Date
- 2023
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/429176
- Identifier
- vital:72565
- Identifier
- 10.11591/ijeecs.v30.i2.pp787-795
- Description
- Nowadays, voluminous and unstructured textual data is found on the Internet that could provide varied valuable information for different institutions such as health care, business-related, training, religion, culture, and history, among others. A such alarming growth of unstructured data fosters the need for various methods and techniques to extract valuable information from unstructured data. However, exploring helpful information to satisfy the needs of the stakeholders becomes a problem due to information overload via the internet. This paper, therefore, presents an effective model for extracting named entities from Ge'ez text using deep learning algorithms. A data set with a total of 5,270 sentences were used for training and testing purposes. Two experimental setups, i.e., long short-term memory (LSTM) and bidirectional long short-term memory (Bi-LSTM) were used to make an empirical evaluation with training and a testing split ratio of 80% to 20%, respectively. Experimental results showed that the proposed model could be a practical solution for building information extraction (IE) systems using Bi-LSTM, reaching a training, validation, and testing accuracy as high as 98.59%, 97.96%, and 96.21%, respectively. The performance evaluation results reflect a promising performance of the model compared with resource-rich languages such as English.
- Format
- 8 pages, pdf
- Language
- English
- Relation
- Indonesian Journal of Electrical Engineering and Computer Science, Gebeyehu, S., Wolde, W. and Shibeshi, Z.S., 2023. Information extraction model from Ge’ez texts. Indonesian Journal of Electrical Engineering and Computer Science, 30(2), pp.787-795, Indonesian Journal of Electrical Engineering and Computer Science volume 30 number 2 787 795 2023 2502-4760
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of Indonesian Journal of Electrical Engineering and Computer Science Statement (https://ijeecs.iaescore.com/index.php/IJEECS/about/editorialPolicies#openAccessPolicy)
- Hits: 115
- Visitors: 120
- Downloads: 8
Collections
Shibeshi, Zelalem Sintayehu (Dr)
RU Department of Computer Science
SDG 09. Industry, Innovation and Infrastructure
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | SOURCE1 | Information extraction model from Ge’ez texts.pdf | 291 KB | Adobe Acrobat PDF | View Details Download |