Design and Develop Amharic Language Interface to Database

Smegnew Asemie; Kassahun Azezew; Birhanu Gardie

doi:10.17485/IJST/v14i44.1178

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Design and Develop Amharic Language Interface to Database

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Indian Journal of Science and Technology

DOI: 10.17485/IJST/v14i44.1178

Year: 2021, Volume: 14, Issue: 44, Pages: 3254-3263

Original Article

Design and Develop Amharic Language Interface to Database

Smegnew Asemie^1,*, Kassahun Azezew¹, Birhanu Gardie¹

¹ School of Computing and informatics, Mizan-Tepi University, Ethiopia

* Corresponding author email: [email protected]

Received Date:15 July 2021, Accepted Date:04 November 2021, Published Date:22 December 2021

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Background/Objectives: Information has become part of our existence and to access the information from database we need to be skilled with database query languages such as SQL. Hence in this study we propose Amharic Language Interface to Database (ALIDB). Here, the request is simple like asking a human to do so in a local language (Amharic). Method: So far, different techniques such as pattern matching, syntax based, semantic grammar based and Intermediate Representation Language systems have been used to develop NLIDB. Among these techniques, the study employed pattern matching and similarity checking for developing Amharic language text retrieval from the Database. Findings: The result of the experiment shows 91% accuracy. However, the scheme has no impact on Amharic temporal queries. Further development will be done on the algorithm that includes temporal queries in ALIDB. Novelty: Finally we identified 20 rules and thereby contributed a new pattern / algorithm for this language that converts Amharic sentence into a Structured Query Language (SQL) and fetch results from the Database.

Keywords: Amharic Language; Database interface; DBMS; NLIDB; NLP

References

Bais H, Machkour M, Koutti L. An independent-domain natural language interface for multimodel databases. International Journal of Computational Intelligence Studies. 2019;8(3):206. Available from: https://www.inderscience.com/info/inarticle.php?artid=102547
Kaur A. PLID-Punjabi Language Interface to Database. THAPAR UNIVERSITY thesis
Asemie S, Mamo G, Kababa T. Possibility of Amharic Query Processing in Database using Natural Language Interface. IJERT . 2017;06. Available from: https://www.ijert.org/possibility-of-amharic-query-processing-in-database-using-natural-language-interface
Kumar A, Kumar AR, Harshitha P, Mahadevaswamy, Sachin DN. Providing Natural Language Interface To Database Using Artificial Intelligence”. International Journal of Scientific & Technology Research. 2019;8(10). Available from: https://www.ijstr.org/final-print/oct2019/Providing-Natural-Language-Interface-To-Database-Using-Artificial-Intelligence-.pdf
Affolter K, Stockinger K, Bernstein A. A comparative survey of recent natural language interfaces for databases. The VLDB Journal. 2019;28(5):793–819. Available from: https://dx.doi.org/10.1007/s00778-019-00567-8
Manaris B. Natural Language Processing: A Human-Computer Interaction Perspective. In: Advances in Computers. (Vol. 47, pp. 1-55) Elsevier. 1998.
Hosu I, Iacob R, Brad F, Ruseti S, Rebedea T. Natural Language Interface for Databases Using a Dual-Encoder Model”, in proc. ICoCL. Santa Fe, New Mexico, USA. 2018.
Yuan C, Ryan PB, Ta C, Guo Y, Li Z, Hardin J, et al. Criteria2Query: a natural language interface to clinical databases for cohort definition. Journal of the American Medical Informatics Association. 2019;26(4):294–305. Available from: https://dx.doi.org/10.1093/jamia/ocy178
Poetra DA, Widagdo TE, Azizah F. NLIDB for Query with Temporal Aspect. International Conference on Data and Software Engineering. 2019. Available from: https://ieeexplore.ieee.org/document/9092618
Ramesh D, Sanampudi SK. Telugu Language Interface to Databases. International Journal of Advanced Research in Computer and Communication EngineeringVol. 2013;2(7). Available from: https://www.ijarcce.com/upload/2013/july/72-o-Suresh%20Kumar-telugu%20language%20interface%20to%20databases.pdf
Wang W, Tian Y, Wang H, Ku WS. A Natural Language Interface for Database: Achieving Transfer-learnability Using Adversarial Method for Question Understanding. 2020 IEEE 36th International Conference on Data Engineering (ICDE). 2020.
Dubey R, Kawale T, Choudhary T, Narawade V. Hindi Language Interface to Database. ITM Web of Conferences. 2020;32:01007. Available from: https://dx.doi.org/10.1051/itmconf/20203201007
Abass Y, Zahoor S, Irfan. Common Database Interface with NLP. International Journal of Computer Science and Mobile Computing. 2017;6(6). Available from: https://www.ijcsmc.com/docs/papers/June2017/V6I6201733.pdf
Tefera YA. ACASN-Automatic Construction of Amharic Semantic Networks from Unstructured Text Using Amharic WordNet. Addisababa University thesis
Belay B, Habtegebrial T, Liwicki M, Belay G, Stricker D. A Blended Attention-CTC Network Architecture for Amharic Text-image Recognition. Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods. 2021;p. 978–989.
Teshome Y. Sentence Level Opinion Mining. thesis
Gashaw I, Shashirekha HL. ML Approaches for Amharic Parts-of-speech Tagging. In: Proc. of ICON-2018. (pp. 69-74) 2018.
AKTT. HANTC-Hierarchical Amharic News Text Classification. Addis Ababa University thesis
Shah D, Vanusha D. Optimizing Natural Language Interface for Relational Database. International Journal of Engineering and Advanced Technology (IJEAT). 2019;08:4.
K DOG, JAA. Semantic Analysis of Natural Language Queries Using Domain Ontology for Information Access from Database. I J Intell Syst Appl. 2013;p. 81–90.
Al-Rababah K, Shatnawi S. An Arabic Language Interface to Databases Using a Morphologically-Based Lexicon, Language Indicators and Pos Tagging. International Journal of Multimedia and Image Processing. 2012;2(1/2):87–95. Available from: https://dx.doi.org/10.20533/ijmip.2042.4647.2012.0011
Liu S, Bhowmick SS, Zhang W, Wang S, Huang W, Joty S, et al. NEURON: Qery Optimization Meets Natural Language Processing For Augmenting Database Education.
Li HVJ, Yang H. NaLIX : an Interactive Natural Language Interface for Querying XML,” in in the proceedings of the SIGMOD, 2005. 2005.

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© 2021 Asemie 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)