Ontology-based knowledge management for technology intensive industries

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Ontology-Based Knowledge Management For Technology Intensive Industries.

This work examines the use of ontologies in knowledge management applications for technology intensive industries. Ontologies represent knowledge maps of specific technology domains and for the purposes of this thesis are deployed to capture, store and assess technological trends and changes. The objective is to improve the capabilities of technology intensive organizations to monitor, assess, predict and respond to technological trends and changes. This thesis presents a variety of ontology engineering methodologies to update dynamically and systematically the content and structure of ontologies. Dynamic ontologies act as advanced business intelligence support for market, products and technology watch and represent a novel knowledge management practice in an area (technology evolution assessment) of tremendous importance to the high technology sector. This thesis also explores the use of Natural Language Processing (NLP) technology in monitoring domain trends. A feedback control structure is presented for the dynamic management and maintenance of ontologies. The idea of Semantic Extension Sets is presented for discovering inner and outer domain mappings. Finally this work concludes with a Knowledge Management Platform for the intelligent monitoring, planning and forecasting of technological evolution in highly dynamic domains

Ontology-Based Knowledge Management for Technology Intensive Industries

This work examines the use of ontologies in knowledge management applications for technology intensive industries. Ontologies represent knowledge maps of specific technology domains and for the purposes of this thesis are deployed to capture, store and assess technological trends and changes. The objective is to improve the capabilities of technology intensive organizations to monitor, assess, predict and respond to technological trends and changes. This thesis presents a variety of ontology engineering methodologies to update dynamically and systematically the content and structure of ontologies. Dynamic ontologies act as advanced business intelligence support for market, products and technology watch and represent a novel knowledge management practice in an area (technology evolution assessment) of tremendous importance to the high technology sector. This thesis also explores the use of Natural Language Processing (NLP) technology in monitoring domain trends. A feedback control structure is presented for the dynamic management and maintenance of ontologies. The idea of Semantic Extension Sets is presented for discovering inner and outer domain mappings. Finally this work concludes with a Knowledge Management Platform for the intelligent monitoring, planning and forecasting of technological evolution in highly dynamic domains