A Comparison Between Ontology-Based and Translation-Based Semantic Search Engines for Arabic Blogs

Al-Safadi, Lilac; Al-Rgebh, Dalal; AlOhali, Wejdan

doi:10.1007/s13369-012-0473-1

Cited by 10 publications

(3 citation statements)

References 8 publications

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“…Al-Safadi et al [22] had proposed a systematic system for an Arab search engine based on the field of ontology, but only within Arab blogs. It categorized the Arabic language into a series of classes, characteristics, and relationships.…”

Section: Previous Workmentioning

confidence: 99%

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Enhanced Search Engine Using Proposed Framework and Ranking Algorithm Based on Semantic Relations

et al. 2019

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Today, most users need search engines to facilitate search and information retrieval processes. Unfortunately, traditional search engines have a significant challenge that they should retrieve high-precision results for a specific unclear query at a minimum response time. Also, a traditional search engine cannot expand a small, ambiguous query based on the meaning of each keyword and their semantic relationship. Therefore, this paper proposes a comprehensive search engine framework that combines the benefits of both a keyword-based and a semantic ontology-based search engine. The main contributions of this work are developing an algorithm for ranking results based on fuzzy membership value and a mathematical model of exploring a semantic relationship between different keywords. In the conducting experiments, eight different test cases were implemented to evaluate the proposed system. Executed test cases have achieved a precision rate of 97% with appropriate response time compared to the relevant systems.

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Section: Previous Workmentioning

confidence: 99%

“…The main benefit of smart semantic search systems is retrieving the most significant results with high precision and lower recall. The returned results from Google had a higher recall than precision rate [8], [15], [22].…”

Section: A Efficiencymentioning

confidence: 99%

Enhanced Search Engine Using Proposed Framework and Ranking Algorithm Based on Semantic Relations

et al. 2019

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“…Ontology-based Models showed a better performance in understanding the user queries and hence the retrieval performance [67]. However, as a result to the lack of a rich Arabic language Ontology [7][8][9][10][11][12][13][14][15][16] and [68] , most researches studies in Ontology-Based FQA focus on specific domain Ontologys that have been built manually or automatically.…”

Section: Hybrid Fqa Modelsmentioning

confidence: 99%

Semantic-based Arabic Question Answering: Core and Recent Techniques

Abaker¹,

Rshwan²

2017

IJUNESST

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Providing the right answer remains a hot research field in Question Answering (QA). Considerable improvements in QA performance were obtained by adopting core semantic techniques like WordNet. However, an ideal adoption of such technique in Arabic QA is quite challenging, particularly for Fatwa QA which answers questions in Islamic religion domain. The point of this review is to overview the state of the art Arabic Fatwa QA models with a focus on the core and recent semantic representation techniques and present a comparative summary that involves QA paradigms, semantic techniques, performance, scope, and limitations. The Aim is to highlight the new directions and open issues regarding the challenges for answering Arabic Fatwa questions on semantics basis. Recent semantic techniques like "Skip-Gram/CBOW" NN embeddings revealed a promising performance compared to a core technique "Ontology" when adopted in some tasks of Arabic Fatwa QA.

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A Framework for Building an Arabic Multi-disciplinary Ontology from Multiple Resources

Hawalah

2017

Cogn Comput

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A Comparison Between Ontology-Based and Translation-Based Semantic Search Engines for Arabic Blogs

Cited by 10 publications

References 8 publications

Enhanced Search Engine Using Proposed Framework and Ranking Algorithm Based on Semantic Relations

Enhanced Search Engine Using Proposed Framework and Ranking Algorithm Based on Semantic Relations

Semantic-based Arabic Question Answering: Core and Recent Techniques

A Framework for Building an Arabic Multi-disciplinary Ontology from Multiple Resources

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