In the context of the IoT one of the current hypes of the (German) machine industry is to provide the content of technical documentation using so called content delivery portals to their customers and service technicians. Goal is to provide detailed, order-specific information directly to electronic devices. The scope goes from XML based technical documentation for user and service manuals over legacy BLOB data to spare part catalogues and CRM systems.
FarsBase, a Farsi Knowledge Graph, consists of more than 500K of entities and 7 million relations between them. Data (triple) have been extracted from Farsi edition of Wikipedia and raw text using NLP techniques. According to the semantic web, RDF data model and OWL2 ontology have been employed to implement the Farsi Knowledge Graph (FKG). Resources and their relations are stored in triple format, therefore, access to the knowledge graph is provided by a SPARQL endpoint.
This paper describes the creation of an RDF ontology designed to sup-port information retrieval needs of journalists and media professionals.
The purpose of the ontology is to complete the automated extensions of query terms by using the relationships between the concepts and terms registered in the ontology. By using this ontology, end-users can identify additional concepts that are related to the selected topic, and incorporate new terms to the query that will be later launched against a full-text indexer based on SOLR.