Comparative Analysis of Automated Text Summarization Techniques: The Case of Ethiopian Languages

Nowadays, there is an abundance of information available from both online and offline sources. For a single topic, we can get more than hundreds sources containing wealth information. The ability to extract or generate summary popular content allows users quickly search for obtain preliminary data in the shortest amount time. Manually extracting useful them difficult task. Automatic text summarization (ATS) systems are being developed address this issue. Text process large documents compressing it into while retaining all relevant contents. This review paper provides broad overview ATS research works various Ethiopian languages such as Amharic, Afan Oromo, Tigrinya using different approaches. work has identified novel recommended state-of-the-art techniques methods future researchers area knowledge support new field by providing concise feature extraction classification required types approaches applied languages. Finally, recommendations have been forwarded.