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Advances in Case-Based Reasoning
The 7th European Conference on Case-Based Reasoning (ECCBR 2004) was held from August 30 through September 2, at the Complutense University of Madrid, Spain. ECCBR was born in Aberdeen, UK (2002), after a series of European workshops held in Trento, Italy(2000), Dublin, Ireland(1998), Lausanne, Switzerland (1996), Paris, France (1994), and Kaiserslautern, Germany (1993). ECCBR is the premier international forum for researchers and practitioners of case-based reasoning (CBR) in the years interleaving with the biennial international counterpart ICCBR, whose 5th edition was held in Trondheim, Norway in 2003. The CBR community has shown for years a deep interest in the application of its researc...
Innovations in Multi-Agent Systems and Application – 1
In today’s world, the increasing requirement for emulating the behavior of real-world applications for achieving effective management and control has necessitated the usage of advanced computational techniques. Computational intelligence-based techniques that combine a variety of problem solvers are becoming increasingly pervasive. The ability of these methods to adapt to the dynamically changing environment and learn in an online manner has increased their usefulness in simulating intelligent behaviors as observed in humans. These intelligent systems are able to handle the stochastic and uncertain nature of the real-world problems. Application domains requiring interaction of people or or...
Advances in Data Mining. Applications and Theoretical Aspects
This book constitutes the refereed proceedings of the 12th Industrial Conference on Data Mining, ICDM 2012, held in Berlin, Germany in July 2012. The 22 revised full papers presented were carefully reviewed and selected from 97 submissions. The papers are organized in topical sections on data mining in medicine and biology; data mining for energy industry; data mining in traffic and logistic; data mining in telecommunication; data mining in engineering; theory in data mining; theory in data mining: clustering; theory in data mining: association rule mining and decision rule mining.
Artificial Intelligence in Medicine
This book constitutes the refereed proceedings of the 20th International Conference on Artificial Intelligence in Medicine, AIME 2022, held in Halifax, NS, Canada, in June 2022. The 39 full papers presented together with 7 short papers were selected from 113 submissions. The papers are grouped in topical sections on knowledge-based system; machine learning; medical image processing; predictive modeling; natural language processing.
Knowledge Discovery, Knowledge Engineering and Knowledge Management
This book constitutes the thoroughly refereed post-conference proceedings of the First International Joint Conference on Knowledge Discovery, Knowledge Engineering, and Knowledge Management, IC3K 2009, held in Funchal, Madeira, Portugal, in October 2009. This book includes revised and extended versions of a strict selection of the best papers presented at the conference; 27 revised full papers together with 3 invited lectures were carefully reviewed and selected from 369 submissions. According to the three covered conferences KDIR 2009, KEOD 2009, and KMIS 2009, the papers are organized in topical sections on on knowledge discovery and information retrieval, knowledge engineering and ontology development, and on knowledge management and information sharing.
Case-Based Reasoning on Images and Signals
This is the first edited book that deals with the special topic of signals and images within Case-Based Reasoning (CBR). Signal-interpreting systems are becoming increasingly popular in medical, industrial, ecological, biotechnological and many other applications. Existing statistical and knowledge-based techniques lack robustness, accuracy and flexibility. New strategies are needed that can adapt to changing environmental conditions, signal variation, user needs and process requirements. Introducing CBR strategies into signal-interpreting systems can satisfy these requirements.
Workflow Modeling Assistance by Case-based Reasoning
Gilbert Müller introduces the foundations of Business Process Management as well as Case-based Reasoning and presents a novel approach to assist the complex, time-consuming, and error-prone task of workflow modeling. By means of methods from artificial intelligence, in particular from the field of Case-based Reasoning, he shows how workflows can be automatically constructed according to a query specified by the user. Thus, the modeling process can be supported substantially, which addresses a highly relevant problem in many workflow domains.
Case-Based Reasoning Research and Development
This book constitutes the refereed proceedings of the 27th International Conference on Case-Based Reasoning Research and Development, ICCBR 2019, held in Otzenhausen, Germany, in September 2019. The 26 full papers presented in this book were carefully reviewed and selected from 43 submissions. 15 were selected for oral presentation and 11 for poster presentation. The theme of ICCBR 2019, "Explainable AI (XAI)," was highlighted by several activities. These papers, which are included in the proceedings, address many themes related to the theory and application of case-based reasoning and its future direction.
Artificial Intelligence in Medicine
This book constitutes the refereed proceedings of the 13th Conference on Artificial Intelligence in Medicine, AIME 2011, held in Bled, Slovenia, in July 2011. The 42 revised full and short papers presented together with 2 invited talks were carefully reviewed and selected from 113 submissions. The papers are organized in topical sections on knowledge-based systems; data mining; special session on AI applications; probabilistic modeling and reasoning; terminologies and ontologies; temporal reasoning and temporal data mining; therapy planning, scheduling and guideline-based care; and natural language processing.
Fusion Methods for Unsupervised Learning Ensembles
The application of a “committee of experts” or ensemble learning to artificial neural networks that apply unsupervised learning techniques is widely considered to enhance the effectiveness of such networks greatly. This book examines the potential of the ensemble meta-algorithm by describing and testing a technique based on the combination of ensembles and statistical PCA that is able to determine the presence of outliers in high-dimensional data sets and to minimize outlier effects in the final results. Its central contribution concerns an algorithm for the ensemble fusion of topology-preserving maps, referred to as Weighted Voting Superposition (WeVoS), which has been devised to improv...
