Knowledge graphs: a new realm of resources discovery system to get more enhanced results

Knowledge graphs: a new realm of resources discovery system to get more enhanced results
The advent of linked data and semantic web technologies resulted in the development of knowledge graphs. The term Knowledge graphs came into existence with the launch of Google Knowledge graph in 2012, which gathers and integrate the data from multiple, heterogeneous sources and formalize the information in order to get the enhanced results.

What is the knowledge graph?

Knowledge graphs can be described as a specific type of databases representing a collection of entities/ concepts ( real-world objects, people, places, events) and their semantic relationships. Entities in knowledge graphs are described in such a manner that their description is interlinked with each other which helps the users in the better search, navigation, retrieval of information and question answering. In technical terminology, it is also called RDF Graph which consists of a set of RDF triples, where each RDF triple (S, P, O) is an ordered set of Subject, Predicate, and Object.

• Knowledge graphs just like other databases support the user in resource discovery, navigation and retrieval of information via structured queries more quickly and efficiently.

• They are not limited to the abstract concepts and relations but can also contain the documents and datasets associated with things.

• RDF, RDF-Schema and W3C's OWL is used for representing knowledge on the web.

• The underlying basis of the Knowledge graph is Ontology which specifies the semantics of data and gives the flexible structure of Knowledge graphs because the ontology can be extended and revised as new data arrives.

• The data in the knowledge graphs can be analyzed and used for visualization purposes.

• The semantic relationship feature of entities described in knowledge graphs lets the user to interpret the data and finding newer facts based on that.

• Knowledge graphs can be curated and enriched by the community-driven editorial process (examples: Wikidata, Freebase).

Examples of Knowledge graphs

References: 

• https://tech.africa/google-knowledge-graph-swahili/  (image) 
• https://www.csee.umbc.edu/courses/graduate/691/fall18/07/ (image)

To know more:

• https://www.ontotext.com/knowledgehub/fundamentals/what-is-a-knowledge-graph/
• https://en.wikipedia.org/wiki/Knowledge_Graph
• https://arxiv.org/pdf/1803.03198.pdf
• http://www.semantic-web-journal.net/system/files/swj1954.pdf

Glossary:

Semantic technology: Semantic Technology defines and links data on the Web (or within an enterprise) by developing languages to express rich, self-describing interrelations of data in a form that machines can process.

Ontology: ontology is “an explicit specification of a conceptualization”. A set of concepts and categories in a subject area or domain that shows their properties and the relations between them.