IMAT: Intelligent Mobile Agent

Dhayne, Houssein; Kilany, Rima; Sabha, Rami Abou

doi:10.1109/imcet.2018.8603059

Cited by 1 publication

(1 citation statement)

References 12 publications

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“…The querying and reasoning of the ontology approach were grounded in SPARQL, as well as RDF query language, and the rules of semantic web rule language (SWRL) were employed for rollover evaluation and to identify proposed measures. Concomitantly, reference [53] presented a framework permitting a large amount of data to be accessed over the internet. An ontology that can hold web resource description was established, and a composition engine of automated servicing was conducted to establish the benefits of the ontology.…”

Section: Ontologymentioning

confidence: 99%

Ontology-Based Approach to Semantically Enhanced Question Answering for Closed Domain: A Review

Arbaaeen

Shah

2021

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For many users of natural language processing (NLP), it can be challenging to obtain concise, accurate and precise answers to a question. Systems such as question answering (QA) enable users to ask questions and receive feedback in the form of quick answers to questions posed in natural language, rather than in the form of lists of documents delivered by search engines. This task is challenging and involves complex semantic annotation and knowledge representation. This study reviews the literature detailing ontology-based methods that semantically enhance QA for a closed domain, by presenting a literature review of the relevant studies published between 2000 and 2020. The review reports that 83 of the 124 papers considered acknowledge the QA approach, and recommend its development and evaluation using different methods. These methods are evaluated according to accuracy, precision, and recall. An ontological approach to semantically enhancing QA is found to be adopted in a limited way, as many of the studies reviewed concentrated instead on NLP and information retrieval (IR) processing. While the majority of the studies reviewed focus on open domains, this study investigates the closed domain.

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Section: Ontologymentioning

confidence: 99%