Building Bilingual Algorithm English-Arabic Ontology for Cognitive Applications

Alnahdi, Amany; Aboalela, Rania; Babour, Amal

doi:10.1109/ieee.iccc.2017.22

Cited by 3 publications

(5 citation statements)

References 4 publications

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“…The methodology used for building the application starts by refining the bi-lingual Arabic-English ontology [1]. Then, the application specifications were determined by deliberating among authors about the best way for presenting the concepts for learning and memorizing terminology.…”

Section: Methodsmentioning

confidence: 99%

“…The ontology [1] was refined to be prepared for use by the mobile application. The refinement process started by displaying all the concepts in a format of a list as can be seen in Figure 1.…”

Section: Methodsmentioning

confidence: 99%

“…The ontologies can combine concepts and be presented using different natural languages. This research presents an improvement for the Bi-Lingual Algorithm ontology proposed and built by [1] to structure knowledge in the Algorithm domain and be presented in both Arabic and English. The designed educational mobile application based on the created ontology for implementation.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, the proposed educational mobile application called ArEnAlg. The application is based on a Bi-Lingual Algorithm ontology [1]. It is built based on the Model-View-Controller (MVC) design pattern [4].…”

Section: Introductionmentioning

confidence: 99%

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ArEnAlg: A Pedagogical Mobile Application for Algorithms Linguistics Based on a Semantic Bilingual Ontology

Alnahdi

Aboalela

Khazmari³

et al. 2022

J. Phys.: Conf. Ser.

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Ontologies are knowledge structures that serve as the foundation for semantic applications. These semantic artifacts organize and classify knowledge to define the semantic relations among the concepts. Some ontologies are constructed for a single natural language, whereas others are built for dual or multi-natural languages. The goal of this study is to design and implement a mobile educational application to help students learn more effectively and to increase the learner’s acquisition of computational linguistics in the Algorithm domain. The methodology is to develop an application with unique features that can display the terms and the concepts in both Arabic and English languages in two different layouts: a list form and a flashcard form. The created app “ArEnAlg” can generate the terms in the algorithm domain. The major objective of the exercise modules is to examine the user’s knowledge of the concepts in the domain of algorithms. The evaluation results tested three factors: the learner’s enjoyment, the acquisition of the computational linguistics, and the application presentation, which showed that behavioral responses support the purpose of the developed application with a max-min range of 99% -81%.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

ArEnAlg: A Pedagogical Mobile Application for Algorithms Linguistics Based on a Semantic Bilingual Ontology

Alnahdi

Aboalela

Khazmari³

et al. 2022

J. Phys.: Conf. Ser.

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show abstract

“…Questions/Answering onym, hypernym, hyponym, meronym, and holonym in an Arabic ontology called Azhary. On the other hand, the authors of in [14] created a specific domain of Arabic Ontology that treats algorithms for the purpose of information retrieval.…”

Section: Morpological Analysismentioning

confidence: 99%

Ontological Approach Based on Multi-Agent System for Indexing and Filtering Arabic Documents

Zouaoui¹,

Rezeg²

2019

Journal of Digital Information Management

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In recent years, Automatic Natural Language Processing (ANLP) for Arabic language has received a great amount of attention for the development of several applications such as question answering, information retrieval and translation, etc. However, there are a few automated applications using Semantic Web technologies for retrieving Arabic-language documents despite the high demand and need for this content. In addition, the Arabic language presents serious challenges to researchers and developers of NLP applications. These challenges are due to the complexity of the morphological, syntactic and semantic characteristics specific to the Arabic text, which requires the use of semantic resources such as ontology. In our work, we propose a new approach based on ontology and multi-agent systems to index and filter Arabic documents. Our proposal is composed of five layers, each layer contains several agents: (1) Lexical Layer; (2) Syntactic Layer; (3) Semantic Layer; (4) Indexing Layer; and GUI/Interface Layer. Our Arabic ontology is manually constructed on the basis of schemes and their semantics meanings. We use also combination of Arabic WordNet contents and Arabic VerbNet in the process of constructing the ontology. We use the semantic similarity to find the relevant documents according to the user's queries. The aim of this paper is to study the effect of patterns in solving the problem of the semantic indexing system (SIS). The main objective is to improve the quality of the indexing process to ensure the accuracy of the information search of relevant documents based on us ers' multiword queries, and also to reduce indexing and search time. Indeed, our experiments are conducted on the basis of the combination of two Arab corpus: OSAC and SemEval. We compared our results Ontological Approach Based on Multi-Agent System for Indexing and Filtering Arabic Documentswith Lucene in-dex for the same data and, we found that our approach achieves much better results than the other.

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A Framework for Building a Multilingual Industrial Ontology: Methodology and a Case Study for Building Smartphone English-Arabic Ontology

Alnahdi¹

2021

IJWesT

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As Web 3.0 is blooming, ontologies augment semantic Web with semi–structured knowledge. Industrial ontologies can help in improving online commercial communication and marketing. In addition, conceptualizing the enterprise knowledge can improve information retrieval for industrial applications. Having ontologies combine multiple languages can help in delivering the knowledge to a broad sector of Internet users. In addition, multi-lingual ontologies can also help in commercial transactions. This research paper provides a framework model for building industrial multilingual ontologies which include Corpus Determination, Filtering, Analysis, Ontology Building, and Ontology Evaluation. It also addresses factors to be considered when modeling multilingual ontologies. A case study for building a bilingual English-Arabic ontology for smart phones is presented. The ontology was illustrated using an ontology editor and visualization tool. The built ontology consists of 67 classes and 18 instances presented in both Arabic and English. In addition, applications for using the ontology are presented. Future research directions for the built industrial ontology are presented.

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Building Bilingual Algorithm English-Arabic Ontology for Cognitive Applications

Cited by 3 publications

References 4 publications

ArEnAlg: A Pedagogical Mobile Application for Algorithms Linguistics Based on a Semantic Bilingual Ontology

ArEnAlg: A Pedagogical Mobile Application for Algorithms Linguistics Based on a Semantic Bilingual Ontology

Ontological Approach Based on Multi-Agent System for Indexing and Filtering Arabic Documents

A Framework for Building a Multilingual Industrial Ontology: Methodology and a Case Study for Building Smartphone English-Arabic Ontology

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