Details

Autor(en) / Beteiligte

• Smirnov, Alexander
• Shilov, Nikolay
• Ponomarev, Andrew
• Bernardino, Jorge
• Fred, Ana
• Aveiro, David
• Salgado, Ana
• Filipe, Joaquim
• Dietz, Jan

Titel

Context-Aware Knowledge Management as an Enabler for Human-Machine Collective Intelligence

Ist Teil von

• Knowledge Discovery, Knowledge Engineering and Knowledge Management, 2022, Vol.1608, p.94-116

Ort / Verlag

Switzerland: Springer International Publishing AG

Erscheinungsjahr

2022

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• The effectiveness of maintaining and accessing decentralized organization’s information and knowledge is crucial for the competitiveness of the company and its ability to adapt to ever-changing business environment. Most of this knowledge is typically scattered across various socio-cyber-physical systems inside the company. The concept of socio-cyber-physical system and the related reseach aims on providing a holistic view on heterogeneous systems, including physical, software and human components and their real-time interactions via multilevel connections. Context-aware knowledge management is becoming de facto one of the essential business strategies to support such systems. Its purpose is to facilitate the transfer and exchange of knowledge in the context of business structures and activities related to cultural norms. This paper discussess emerging trends (including role organization, dynamic motivation mechanisms, and multidimensional ontology) in knowledge management for socio-cyber-physical systems. These trends can contribute to the creation of an innovative IT and HR environment based on the collective intelligence of humans and machines, where information and knowledge is shared among participants and among collectives of participants who can be either humans (collective intelligence as methods used by humans to take collective action to solve problems) or software services (based on artificial intelligence models). The paper discusses examples of trends and experiences of their implementation in a global manufacturing company and also proposes a concept human-machine collective intelligence environment utilizing the discussed technologies to support human-computer collaboration in decision support scenarios.