Agent-supported knowledge acquisition for digital humanities research

Computer-based information processing tools face many challenges in the field of digital humanities, especially in literary studies. Big data and knowledge acquisition methods often could not cope with texts from the distant past. To solve the problem a multi-agent information processing framework is proposed that performs preprocessing tasks to increase the quality of knowledge acquisition methods. The framework is part of a cloud-based research platform, also presented in this paper. The platform provides shared document and data storage, programmable statistical analysis and on-line publishing tools.