NDLI: Semantic Protocol and Resource Description Framework Query Language: A Comprehensive Review

Semantic Protocol and Resource Description Framework Query Language: A Comprehensive Review

Content Provider	Directory of Open Access Journals (DOAJ)
Author	Essam H. Houssein Nahed Ibrahem Alaa M. Zaki Awny Sayed
Abstract	This review presents various perspectives on converting user keywords into a formal query. Without understanding the dataset's underlying structure, how can a user input a text-based query and then convert this text into semantic protocol and resource description framework query language (SPARQL) that deals with the resource description framework (RDF) knowledge base? The user may not know the structure and syntax of SPARQL, a formal query language and a sophisticated tool for the semantic web (SEW) and its vast and growing collection of interconnected open data repositories. As a result, this study examines various strategies for turning natural language into formal queries, their workings, and their results. In an Internet search engine from a single query, such as on Google, numerous matching documents are returned, with several related to the inquiry while others are not. Since a considerable percentage of the information retrieved is likely unrelated, sophisticated information retrieval systems based on SEW technologies, such as RDF and web ontology language (OWL), can help end users organize vast amounts of data to address this issue. This study reviews this research field and discusses two different approaches to show how users with no knowledge of the syntax of semantic web technologies deal with queries.
e-ISSN	22277390
DOI	10.3390/math10173203
Journal	Mathematics
Issue Number	3203
Volume Number	10
Language	English
Publisher	MDPI AG
Publisher Date	2022-01-01
Publisher Place	Switzerland
Access Restriction	Open
Subject Keyword	Mathematics Semantic Web Sparql Query Resource Description Framework (rdf) Question Answering System (qas) Semantic Question Answering (sqa) Web Ontology Language (owl)
Content Type	Text
Resource Type	Article

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