Automatic Text Summarization for Amharic Legal Judgments
| dc.contributor.advisor | Alemayehu, Nega | |
| dc.contributor.author | Adane, Helene | |
| dc.date.accessioned | 2020-06-08T07:24:35Z | |
| dc.date.accessioned | 2023-11-18T12:45:19Z | |
| dc.date.available | 2020-06-08T07:24:35Z | |
| dc.date.available | 2023-11-18T12:45:19Z | |
| dc.date.issued | 2006-09 | |
| dc.description.abstract | With the continuing fast growth of information and data today, it has become more and mo re urgent and important to find proper information efficiently, with some improved mechanisms Nowadays, people need much more information in work and life. The use of information techno logy such as the Internet makes information more easily accessible. However, people are having problems to easily get the information they want in a summarized way without wasting their time in the vast load of information made available to them . Thus, automatic text summarization draws substantial interest s incest provides a solution to the information overload problem people face in this digit al era. This work is concentrated on producing a prototype system of text summarization on Amharic legal judgments. The methodology employed is an extraction technique. Amharic legal judgments rendered by the supreme court of Ethiopia are selected in consultation with legal experts (lawyers , law instructor & students). The data selected in this manner are employed to generate the summaries Sentences in each judgment are classified in to different unit s according to their argumentative roles. From each argumentative unit , sentences with the highest weight at 20 % compression rate are extracted and presented as a summary . To evaluate the performance of the system, a random summary at similar compression rate is generated. Using extrinsic evaluation technique, the performance of the system summary and the random summary were compared with an ideal summary (human generated summary). The results obtained from the system are promising when compared with the random summary. To improve the performance of the system, sentences at 10% compression rate were extracted and the system's performance has improved. Therefore, the sentences extracted by the system summary using different extraction features are much closer to the manual (ideal) summary. The prototype text summarize has been developed using the Python programming language as a tool. | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/12345678/21457 | |
| dc.language.iso | en | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | Information Science | en_US |
| dc.title | Automatic Text Summarization for Amharic Legal Judgments | en_US |
| dc.type | Thesis | en_US |