Customer service agents play an important role in bridging the gap between customers’ vocabulary and business terms. In a scenario where organisations are moving into semi-automatic customer service, se- mantic technologies with capacity to bridge this gap become a necessity. In this paper we explore the use of automatic taxonomy extraction from text as a means to reconstruct a customer-agent taxonomic vocabulary.
Insight Centre for Data Analytics, National University of Ireland, Galway
https://www.insight-centre.org/
Insight Centre for Data Analytics, National University of Ireland, Galway
https://www.insight-centre.org/
Insight Centre for Data Analytics, National University of Ireland, Galway
https://www.insight-centre.org/
Insight Centre for Data Analytics, National University of Ireland, Galway
https://www.insight-centre.org/
Insight Centre for Data Analytics, National University of Ireland, Galway
https://www.insight-centre.org/
Based on case studies with telecommunication manufacturers and innovators RFS and Nokia, this presentation will show how a knowledge graph based technology supports enterprises to establish transparency for their product and process data without the need of inflexible and expensive master data management or data migration projects. It also shows how sales and product distribution processes get simplified and accelerated, leading to a significant reduction of lead times while increasing inventory turnover.
eccenca GmbH
https://www.eccenca.com
As an experienced data and knowledge engineer at eccenca, Markus is responsible for customer projects focussing on digital supply chain management. He also drives the further development of the eccenca knowledge graph platform Corporate Memory in regards to supply chain requirements, including the APICS / ASCM supply chain ontology for SCOR.
