Ontology-Based Semantic Annotation of Arabic Language Text

Al-Yahya, Maha; Al-Shaman, Mona; Al-Otaiby, Nehal; Al-Sultan, Wafa; Alzahrani, Asma; Al-Dalbahie, Mesheal

doi:10.5815/ijmecs.2015.07.07

Cited by 11 publications

(4 citation statements)

References 14 publications

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“…The core of their annotation system consists of three main modules namely text preprocessing module, semantic annotation module and annotation management module. Al-Yahya et al 11 presented SemTree ontology which is ontology for lexical semantic relation annotations for Arabic text. They developed a prototype system to evaluate the usefulness of SemTree ontology.…”

Section: Related Workmentioning

confidence: 99%

Semantic Annotation of Arabic Web Resources Using Semantic Web Services

Albukhitan

Al-Nazer

Helmy

2016

Procedia Computer Science

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The vision of semantic Web is to have a Web of things instead of Web of documents in a form that can be processed by machines. This vision could be achieved on the existing Web using semantic annotation based on common and public ontologies. Due to exponential growth and huge size of the Web sources, there is a need to have fast and automatic semantic annotation services of Web documents. Since Arabic language received less attention in semantic Web research as compared to Latin languages especially in the field of semantic annotation. This motivates us in this paper to present semantic Web services that support the semantic annotation of Arabic language documents. The services accept documents and ontologies and produce annotations of these documents using different output formats. The proposed services could be used for building semantic Web applications and semantic search engines for Arabic Language. To evaluate the performance of these services, a set of ontologies were used with pre-annotated documents related to those ontologies. The initial results show a promising performance which will support the research in the semantic Web with respect to Arabic language.

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Section: Related Workmentioning

confidence: 99%

Semantic Annotation of Arabic Web Resources Using Semantic Web Services

Albukhitan

Al-Nazer

Helmy

2016

Procedia Computer Science

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“…To test the framework, the authors chose ten news Arabic articles and manually annotated them. After that, in 2015, Al-Yahya et al [16] presented a lexical semantic annotation based on an ontology that contains six classes that build a three-level hierarchical structure. The higher level is Linguistic Concepts, and the lower level is Words.…”

Section: Related Workmentioning

confidence: 99%

An Ontology-driven DBpedia Quality Enhancement to Support Entity Annotation for Arabic Text

Kahlawi¹

2023

IJACSA

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Improving NLP outputs by extracting structured data from unstructured data is crucial, and several tools are available for the English language to achieve this objective. However, little attention has been paid to the Arabic language. This research aims to address this issue by enhancing the quality of DBpedia data. One limitation of DBpedia is that each resource can belong to multiple types and may not represent the intended concept. Additionally, some resources may be assigned incorrect types. To overcome these limitations, this study proposes creating a new ontology to represent Arabic data using the DBpedia ontology, followed by an algorithm to verify type assignments using the resource's title metadata and similarity between resources' descriptions. Finally, the research builds an entity annotation tool for Arabic using the verified dataset.

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“…The most recent Arabic ontology works on Semantic Web can be classified into two categories : The first one, works aimed at building a tool or developing a method for improving several tasks such as : information retrieval [16], translation between languages [15], Educational Applications [40], improving question answering systems [46], [53], morphology Analysis [34], text summarization [17], text annotation [9], and developing Arabic Semantic Search Engine [45].…”

Section: Non-islamic Domainmentioning

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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Ontology-Based Semantic Annotation of Arabic Language Text

Cited by 11 publications

References 14 publications

Semantic Annotation of Arabic Web Resources Using Semantic Web Services

Semantic Annotation of Arabic Web Resources Using Semantic Web Services

An Ontology-driven DBpedia Quality Enhancement to Support Entity Annotation for Arabic Text

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

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