A Look at Semantic Web Technology and the Potential Semantic …
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several standard standards such as Resource Description Framework (RDF), which
is a model for describing all data. Even RDF Schema (RDFS), which creates vocabularies and descriptive term sets. Or yet OWL (Web Ontology Language), which is
a language for creating ontologies that support logical processing, clustering, and
data inference, and Protocol. Or the same RDF Query Language (SPARQL), which
allows obtaining information from RDF graphs [24–26].
However, there is not yet a consensual definition of Semantic Web, it is seen as
a vision that through the idealization of having web data defined and linked can
be used by machines for intentions of integration, automation, and reuse between
distinct applications, and not for display purposes only. The semantic web extends
the principles of documents found on the web to data. In short, Semantic Web is a
new step in the development of the Internet marked by intelligent user interaction
with the web as well as the material made available on it mainly by the organization
of all this content. It is the technology of a new step in the internet transforming the
virtual network. of information in an increasingly human environment [27].
The characteristic of the Semantic Web that best defines it is that it is machinereadable content in which information is given well-defined meaning. Allowing
computers and people to work better together to enrich research and the exploitation
of results on the web. The development of search engines and their progressive integration with social networks tailored to the specific needs of companies, along with
the growing adoption by e-commerce sites optimizing the target of relevant information. Still improving referral of a site through Search Engine Optimization (SEO),
helping to optimize marketing targeting, are aspects of semantic web technologies
that continue to rise, encompassing a huge and beneficial environment of interest to
technology giants [28, 29].
The reality seen and known is that most of the Internet content is meant to
be consumed by possibly not fully understandable by programs. What through
computers can analyze web pages in structural terms, such as checking the web
of links that connect the pages to each other but not yet reliably processing their
meaning. As far as the limitations of today’s web are concerned, the fact that through
the Semantic Web being evolved and widespread will result in structuring the content
of most “machine-readable” web pages. This context creates an environment where
software can perform sophisticated tasks for users when scrolling through the pages.
Just as for this technology to be fully operational, computers must have sets of
inference rules and access to structured collections of information. So, they can have
“automated reasoning”, but technologies for this purpose have evolved over the years.
Reflecting on years of studies and research of Artificial Intelligence, as well as its
Machine and Deep Learning aspects, together with Big Data, making this reality of
digital reasoning ever more real [1, 30].
Unlike the initial bias due to its idealization, related to research focused on centralized systems, which required all users to share the same definitions of concepts
and rules. Which was redirected to this focus giving the breadth of knowledge that
is desired to represent on the Web, and the Semantic Web focused on integrating
distinct representations and decentralizing knowledge representation. Approaching
the modern-day context where knowledge related to “that the computer can read” has
63
several standard standards such as Resource Description Framework (RDF), which
is a model for describing all data. Even RDF Schema (RDFS), which creates vocabularies and descriptive term sets. Or yet OWL (Web Ontology Language), which is
a language for creating ontologies that support logical processing, clustering, and
data inference, and Protocol. Or the same RDF Query Language (SPARQL), which
allows obtaining information from RDF graphs [24–26].
However, there is not yet a consensual definition of Semantic Web, it is seen as
a vision that through the idealization of having web data defined and linked can
be used by machines for intentions of integration, automation, and reuse between
distinct applications, and not for display purposes only. The semantic web extends
the principles of documents found on the web to data. In short, Semantic Web is a
new step in the development of the Internet marked by intelligent user interaction
with the web as well as the material made available on it mainly by the organization
of all this content. It is the technology of a new step in the internet transforming the
virtual network. of information in an increasingly human environment [27].
The characteristic of the Semantic Web that best defines it is that it is machinereadable content in which information is given well-defined meaning. Allowing
computers and people to work better together to enrich research and the exploitation
of results on the web. The development of search engines and their progressive integration with social networks tailored to the specific needs of companies, along with
the growing adoption by e-commerce sites optimizing the target of relevant information. Still improving referral of a site through Search Engine Optimization (SEO),
helping to optimize marketing targeting, are aspects of semantic web technologies
that continue to rise, encompassing a huge and beneficial environment of interest to
technology giants [28, 29].
The reality seen and known is that most of the Internet content is meant to
be consumed by possibly not fully understandable by programs. What through
computers can analyze web pages in structural terms, such as checking the web
of links that connect the pages to each other but not yet reliably processing their
meaning. As far as the limitations of today’s web are concerned, the fact that through
the Semantic Web being evolved and widespread will result in structuring the content
of most “machine-readable” web pages. This context creates an environment where
software can perform sophisticated tasks for users when scrolling through the pages.
Just as for this technology to be fully operational, computers must have sets of
inference rules and access to structured collections of information. So, they can have
“automated reasoning”, but technologies for this purpose have evolved over the years.
Reflecting on years of studies and research of Artificial Intelligence, as well as its
Machine and Deep Learning aspects, together with Big Data, making this reality of
digital reasoning ever more real [1, 30].
Unlike the initial bias due to its idealization, related to research focused on centralized systems, which required all users to share the same definitions of concepts
and rules. Which was redirected to this focus giving the breadth of knowledge that
is desired to represent on the Web, and the Semantic Web focused on integrating
distinct representations and decentralizing knowledge representation. Approaching
the modern-day context where knowledge related to “that the computer can read” has