Eyke Hüllermeier Livres

Case-based reasoning (CBR) is a pivotal methodology in artificial intelligence that addresses new challenges by drawing on previously solved similar problems. It operates on the principle that past experiences, represented as cases, can inform solutions to current issues. This approach hinges on the assumption that similar problems tend to have analogous solutions, allowing for effective generalization and problem-solving based on historical data.

This book constitutes the refereed proceedings of the 23rd International Conference on Case-Based Reasoning Research and Development, ICCBR 2015, held in Frankfurt am Main, Germany, in September 2015.The 26 revised full papers presented were carefully reviewed and selected from 37 submissions.

This book constitutes the refereed proceedings of the 6th International Conference on Scalable Uncertainty Management, SUM 2012, held in Marburg, Germany, in September 2012. The 41 revised full papers and 13 revised short papers were carefully reviewed and selected from 75 submissions. The papers cover topics in all areas of managing and reasoning with substantial and complex kinds of uncertain, incomplete or inconsistent information including applications in decision support systems, machine learning, negotiation technologies, semantic web applications, search engines, ontology systems, information retrieval, natural language processing, information extraction, image recognition, vision systems, data and text mining, and the consideration of issues such as provenance, trust, heterogeneity, and complexity of data and knowledge.

Constitutes the refereed proceedings of the 13th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2010, held in Dortmund, Germany from June 28 - July 2, 2010.