Author ORCID Identifier

https://orcid.org/ 0000-0002-4420-1029

Document Type

Article

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

Computer Sciences

Publication Details

iiWAS 2021

Abstract

While industrial Knowledge Graphs enable information extraction from massive data volumes creating the backbone of the Semantic Web, the specialised, custom designed knowledge graphs focused on enterprise specific information are an emerging trend. We present “KnowText”, an application that performs automatic generation of custom Knowledge Graphs from unstructured text and enables fast information extraction based on graph visualisation and free text query methods designed for non-specialist users. An OWL ontology automatically extracted from text is linked to the knowledge graph and used as a knowledge base. A basic ontological schema is provided including 16 Classes and Data type Properties. The extracted facts and the OWL ontology can be downloaded and further refined. KnowText is designed for applications in business (CRM, HR, banking). Custom KG can serve for locally managing existing data, often stored as “sensitive” information or proprietary accounts, which are not on open web access. KnowText deploys a custom KG from a collection of text documents and enable fast information extraction based on its graph based visualisation and text based query methods.

DOI

https://doi.org/10.21427/m5c6-6t23

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