• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology


Indian Journal of Science and Technology

Year: 2021, Volume: 14, Issue: 38, Pages: 2946-2952

Original Article

An Integrated Development of a Query-Based Document Summarization for Afaan Oromo Using Morphological Analysis

Received Date:26 June 2021, Accepted Date:28 September 2021, Published Date:18 November 2021


Objective: To develop document summarization for the Afaan Oromo language based on the query entered by the user(s). Methods: This study follows the design science analysis technique as a result of its considerations of thoughtful, intellectual, and ingenious activity throughout problem-solving and the creation of knowledge. The developed query-based framework has used the TF-IDF term weight methodology. Development tools such as HornMorpho are employed for morphological analysis; whereas, Natural Language Processing Toolkit is employed for the text process. The system has experimented on the various extraction rates of 10%, 20%, and 30%. The result’s evaluated exploitation recall, precision, and F-measure for objective analysis; whereas, subjective analysis has been evaluated by language consultants. Findings: The results of the evaluations showed that the proposed system registered f-measure of 90%, 91% and 93% at a summary extraction rate of 10%, 20%, and 30% respectively. The informativeness and coherence of the proposed system also registered its best performance summary of 51.67%, 56.67 % and 54.17% average score on five scale measures at an extraction rate of 10%, 20%, and 30% respectively when both methods were used together. Novelty: By using a morphological analysis tool the performance of the system is improved from 80.67% to 91.3% F-measure when we compare it with the previous work even supposing there’s still a requirement to conduct additional analysis to enhance the Afaan Oromo text summarization.

Keywords: Document; Summary; Natural Language Processing; Morphological Analysis; Text Ranking


  1. Manju K, Peter SD, Idicula S. A Framework for Generating Extractive Summary from Multiple Malayalam Documents. Information. 2021;12(1):41. Available from: https://dx.doi.org/10.3390/info12010041
  2. Asthana A, Tiwari EV, Pandey E, Misra EA. A Novel Architecture for Agent Based Text Summarization. 2017.
  3. DebeleDinegde G, Tachbelie MY. Afan Oromo News Text Summarizer. International Journal of Computer Applications. 2014;103(4):1–6. Available from: https://dx.doi.org/10.5120/18059-8990
  4. Naidu R, Bharti SK, Babu KS, Mohapatra RK. Text Summarization with Automatic Keyword Extraction in Telugu e-Newspapers. Smart Computing and Informatics. 2018;77:555–564.


© 2021 Jilo et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)


Subscribe now for latest articles and news.