AOQAS: Ontology Based Question Answering System for Agricultural Domain
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A8995PN5X" target="_blank" >RIV/00216208:11320/25:8995PN5X - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200978597&partnerID=40&md5=f2f6d3a2c788c5a2c7cdd28da116a82c" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200978597&partnerID=40&md5=f2f6d3a2c788c5a2c7cdd28da116a82c</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
AOQAS: Ontology Based Question Answering System for Agricultural Domain
Original language description
Agriculture is an indispensable sector for human community that has been transformed by technological innovations. The data handling with information extraction is one of the areas that is benefited by the advancements in information technology. The presented research work aims to develop a question answering system (QAS) for improving the information retrieval from the agricultural text documents. The proposed Agriculture domain Ontology based QAS (AOQAS) processes the given agricultural text documents and constructs it to a knowledge representation called ontology. The domain based ontology is created using the Bidirectional Encoder Representations from Transformers model (BERT model) with Regular Expressions (RE) for withdrawing domain terms and the Bidirectional Long Short Term Memory model (BiLSTM) with RE for relationship extraction between the agricultural terms. From the developed ontology, the answers for the input query are extracted and validated using Natural Language Processing (NLP) techniques and the deep learning model. The proposed AOQAS shows an accuracy and recall of 98.47% and 98.26%. The outcomes of AOQAS shows better performance when it is evaluated against the current systems. © Cerebration Science Publishing.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Computer Information Systems and Industrial Management Applications
ISSN
2150-7988
e-ISSN
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Volume of the periodical
16
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
16
Pages from-to
230-245
UT code for WoS article
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EID of the result in the Scopus database
2-s2.0-85200978597