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Case-Based Reasoning Research and Development: 4th International Conference on Case-Based Reasoning, ICCBR 2001 Vancouver, BC, Canada, July 30 - August 2, 2001 Proceedings (Lecture Notes in Computer Science #2080)

The 2001 International Conference on Case-Based Reasoning (ICCBR 2001, www.iccbr.org/iccbr01), the fourth in the biennial ICCBR series (1995 in Sesimbra, Portugal; 1997 in Providence, Rhode Island (USA); 1999 in Seeon, Germany), was held during 30 July – 2 August 2001 in Vancouver, Canada. ICCBR is the premier international forum for researchers and practitioners of case based reasoning (CBR). The objectives of this meeting were to nurture significant, relevant advances made in this field (both in research and application), communicate them among all attendees, inspire future advances, and continue to support the vision that CBR is a valuable process in many research disciplines, both computational and otherwise. ICCBR 2001 was the first ICCBR meeting held on the Pacific coast, and we used the setting of beautiful Vancouver as an opportunity to enhance participation from the Pacific Rim communities, which contributed 28% of the submissions. During this meeting, we were fortunate to host invited talks by Ralph Bergmann, Ken Forbus, Jaiwei Han, Ramon López de Mántaras, and Manuela Veloso. Their contributions ensured a stimulating meeting; we thank them all.

Case-Based Reasoning Research and Development: Third International Conference on Case-Based Reasoning, ICCBR-99, Seeon Monastery, Germany, July 27-30, 1999, Proceedings (Lecture Notes in Computer Science #1650)

The biennial International Conference on Case-Based Reasoning (ICCBR) - ries, which began in Sesimbra, Portugal, in 1995, was intended to provide an international forum for the best fundamental and applied research in case-based reasoning (CBR). It was hoped that such a forum would encourage the g- wth and rigor of the eld and overcome the previous tendency toward isolated national CBR communities. The foresight of the original ICCBR organizers has been rewarded by the growth of a vigorous and cosmopolitan CBR community. CBR is now widely recognized as a powerful and important computational technique for a wide range of practical applications. By promoting an exchange of ideas among CBR researchers from across the globe, the ICCBR series has facilitated the broader acceptance and use of CBR. ICCBR-99 has continued this tradition by attracting high-quality research and applications papers from around the world. Researchers from 21 countries submitted 80 papers to ICCBR-99. From these submissions, 17 papers were selected for long oral presentation, 7 were accepted for short oral presentation, and 19 papers were accepted as posters. This volume sets forth these 43 papers, which contain both mature work and innovative new ideas.

Case-Based Reasoning Research and Development: 29th International Conference, ICCBR 2021, Salamanca, Spain, September 13–16, 2021, Proceedings (Lecture Notes in Computer Science #12877)

This book constitutes the proceedings of the 29th International Conference on Case-Based Reasoning, ICCBR 2021, which took place in Salamanca, Spain, during September 13-16, 2021. The 21 papers presented in this volume were carefully reviewed and selected from 85 submissions. They deal with AI and related research focusing on comparison and integration of CBR with other AI methods such as deep learning architectures, reinforcement learning, lifelong learning, and eXplainable AI (XAI).

Case-Based Reasoning Research and Development: 5th International Conference on Case-Based Reasoning, ICCBR 2003, Trondheim, Norway, June 23-26, 2003, Proceedings (Lecture Notes in Computer Science #2689)

The refereed proceedings of the 5th International Conference on Case-Based Reasoning, ICCBR 2003, held in Trondheim, Norway, in June 2003. The 51 revised full papers presented were carefully reviewed and selected from 92 submissions. All current aspects of CBR are addressed including case representation, similarity retrieval, adaptation, case library maintenance, multi-agent collaborative systems, data mining, soft computing, recommender systems, knowledge management, legal reasoning, software reuse, and music.

Case-Based Reasoning Research and Development: 24th International Conference, ICCBR 2016, Atlanta, GA, USA, October 31 - November 2, 2016, Proceedings (Lecture Notes in Computer Science #9969)

This book constitutes the refereed proceedings of the 24th International Conference on Case-Based Reasoning Research and Development, ICCBR 2016, held in Atlanta, GA, USA, in October/November 2016.The 14 revised full papers presented were carefully reviewed and selected from 44 submissions. The papers cover a wide range of CBR topics that are of interest both to researchers and practitioners from foundations of Case-Based Reasoning; over CBR systems for specific tasks and related fields; up to CBR systems, applications and lessons learned in specific areas of expertise such as health; e-science; finance; energy, logistics, traffic; game/AI; cooking; diagnosis, technical support; as well as knowledge and experience management.

Case-Based Reasoning Research and Development: 27th International Conference, ICCBR 2019, Otzenhausen, Germany, September 8–12, 2019, Proceedings (Lecture Notes in Computer Science #11680)

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.

Case-Based Reasoning Research and Development: 26th International Conference, Iccbr 2018, Stockholm, Sweden, July 9-12, 2018, Proceedings (Lecture Notes in Computer Science #11156)

This book constitutes the refereed proceedings of the 26th International Conference on Case-Based Reasoning Research and Development, ICCBR 2018, held in Stockholm, Sweden, in July 2018. The 39 full papers presented in this book were carefully reviewed and selected from 77 submissions. The theme of ICCBR-2017, "The Future of CBR", 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. Topics included multiple papers on textual CBR and a number of cognitive and human oriented papers as well as hybrid research between CBR and machine learning.

Case-Based Reasoning Research and Development: 8th International Conference on Case-Based Reasoning, ICCBR 2009 Seattle, WA, USA, July 20-23, 2009 Proceedings (Lecture Notes in Computer Science #5650)

This book constitutes the refereed proceedings of the 8th International Conference on Case-Based Reasoning, ICCBR 2009, held in Seattle, WA, USA, in July 2009. The 17 revised full papers and 17 revised poster papers presented together with 2 invited talks were carefully reviewed and selected from 55 submissions. Covering a wide range of CBR topics of interest both to practitioners and researchers, the papers are devoted to theoretical/methodological as well as to applicative aspects of current CBR analysis.

Case-Based Reasoning Research and Development: 6th International Conference on Case-Based Reasoning, ICCBR 2005, Chicago, IL, USA, August 23-26, 2005, Proceedings (Lecture Notes in Computer Science #3620)

Case-Based Reasoning Research and Development: 28th International Conference, ICCBR 2020, Salamanca, Spain, June 8–12, 2020, Proceedings (Lecture Notes in Computer Science #12311)

This book constitutes the refereed proceedings of the 28th International Conference on Case-Based Reasoning Research and Development, ICCBR 2020, held in Salamanca, Spain*, in June 2020. The 20 full papers and 2 short papers presented in this book were carefully reviewed and selected from 64 submissions. The theme of ICCBR 2020, “CBR Across Bridges” 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. *The conference was held virtually due to the COVID-19 pandemic.

Case-Based Reasoning Research and Development: 7th International Conference on Case-Based Reasoning, ICCBR 2007 Belfast Northern Ireland, UK, August 13-16, 2007 Proceedings (Lecture Notes in Computer Science #4626)

The refereed proceedings of the 7th International Conference on Case-Based Reasoning are presented in this volume. Fifteen full research papers and eighteen poster papers are presented along with three invited talks. The papers address all aspects of case-based reasoning, featuring original theoretical research, applied research, and applications with practical, social, environmental, and economic significance.

Case Studies in Applied Bayesian Data Science: CIRM Jean-Morlet Chair, Fall 2018 (Lecture Notes in Mathematics #2259)

Presenting a range of substantive applied problems within Bayesian Statistics along with their Bayesian solutions, this book arises from a research program at CIRM in France in the second semester of 2018, which supported Kerrie Mengersen as a visiting Jean-Morlet Chair and Pierre Pudlo as the local Research Professor. The field of Bayesian statistics has exploded over the past thirty years and is now an established field of research in mathematical statistics and computer science, a key component of data science, and an underpinning methodology in many domains of science, business and social science. Moreover, while remaining naturally entwined, the three arms of Bayesian statistics, namely modelling, computation and inference, have grown into independent research fields. While the research arms of Bayesian statistics continue to grow in many directions, they are harnessed when attention turns to solving substantive applied problems. Each such problem set has its own challenges and hence draws from the suite of research a bespoke solution. The book will be useful for both theoretical and applied statisticians, as well as practitioners, to inspect these solutions in the context of the problems, in order to draw further understanding, awareness and inspiration.

Case Studies in Bayesian Methods for Biopharmaceutical CMC (Chapman & Hall/CRC Biostatistics Series)

The subject of this book is applied Bayesian methods for chemistry, manufacturing, and control (CMC) studies in the biopharmaceutical industry. The book has multiple authors from industry and academia, each contributing a case study (chapter). The collection of case studies covers a broad array of CMC topics, including stability analysis, analytical method development, specification setting, process development and optimization, process control, experimental design, dissolution testing, and comparability studies. The analysis of each case study includes a presentation of code and reproducible output. This book is written with an academic level aimed at practicing nonclinical biostatisticians, most of whom have graduate degrees in statistics. • First book of its kind focusing strictly on CMC Bayesian case studies • Case studies with code and output • Representation from several companies across the industry as well as academia • Authors are leading and well-known Bayesian statisticians in the CMC field • Accompanying website with code for reproducibility • Reflective of real-life industry applications/problems

Case Studies in Bayesian Methods for Biopharmaceutical CMC (Chapman & Hall/CRC Biostatistics Series)

The subject of this book is applied Bayesian methods for chemistry, manufacturing, and control (CMC) studies in the biopharmaceutical industry. The book has multiple authors from industry and academia, each contributing a case study (chapter). The collection of case studies covers a broad array of CMC topics, including stability analysis, analytical method development, specification setting, process development and optimization, process control, experimental design, dissolution testing, and comparability studies. The analysis of each case study includes a presentation of code and reproducible output. This book is written with an academic level aimed at practicing nonclinical biostatisticians, most of whom have graduate degrees in statistics. • First book of its kind focusing strictly on CMC Bayesian case studies • Case studies with code and output • Representation from several companies across the industry as well as academia • Authors are leading and well-known Bayesian statisticians in the CMC field • Accompanying website with code for reproducibility • Reflective of real-life industry applications/problems

Case Studies in Bayesian Statistical Modelling and Analysis (Wiley Series in Probability and Statistics #999)

Provides an accessible foundation to Bayesian analysis using real world models This book aims to present an introduction to Bayesian modelling and computation, by considering real case studies drawn from diverse fields spanning ecology, health, genetics and finance. Each chapter comprises a description of the problem, the corresponding model, the computational method, results and inferences as well as the issues that arise in the implementation of these approaches. Case Studies in Bayesian Statistical Modelling and Analysis: Illustrates how to do Bayesian analysis in a clear and concise manner using real-world problems. Each chapter focuses on a real-world problem and describes the way in which the problem may be analysed using Bayesian methods. Features approaches that can be used in a wide area of application, such as, health, the environment, genetics, information science, medicine, biology, industry and remote sensing. Case Studies in Bayesian Statistical Modelling and Analysis is aimed at statisticians, researchers and practitioners who have some expertise in statistical modelling and analysis, and some understanding of the basics of Bayesian statistics, but little experience in its application. Graduate students of statistics and biostatistics will also find this book beneficial.

Case Studies in Bayesian Statistical Modelling and Analysis (Wiley Series in Probability and Statistics)

Provides an accessible foundation to Bayesian analysis using real world models This book aims to present an introduction to Bayesian modelling and computation, by considering real case studies drawn from diverse fields spanning ecology, health, genetics and finance. Each chapter comprises a description of the problem, the corresponding model, the computational method, results and inferences as well as the issues that arise in the implementation of these approaches. Case Studies in Bayesian Statistical Modelling and Analysis: Illustrates how to do Bayesian analysis in a clear and concise manner using real-world problems. Each chapter focuses on a real-world problem and describes the way in which the problem may be analysed using Bayesian methods. Features approaches that can be used in a wide area of application, such as, health, the environment, genetics, information science, medicine, biology, industry and remote sensing. Case Studies in Bayesian Statistical Modelling and Analysis is aimed at statisticians, researchers and practitioners who have some expertise in statistical modelling and analysis, and some understanding of the basics of Bayesian statistics, but little experience in its application. Graduate students of statistics and biostatistics will also find this book beneficial.

Case Studies in Bayesian Statistics: Volume III (Lecture Notes in Statistics #121)

This third volume of case studies presents detailed applications of Bayesian statistical analysis, emphasising the scientific context. The papers were presented and discussed at a workshop held at Carnegie-Mellon University, and this volume - dedicated to the memory of Morrie Groot-reproduces six invited papers, each with accompanying invited discussion, and nine contributed papers with the focus on econometric applications.

Case Studies in Bayesian Statistics (Lecture Notes in Statistics #83)

The past few years have witnessed dramatic advances in computational methods for Bayesian inference. As a result, Bayesian approaches to solving a wide variety of problems in data analysis and decision-making have become feasible, and there is currently a growth spurt in the application of Bayesian methods. The purpose of this volume is to present several detailed examples of applications of Bayesian thinking, with an emphasis on the scientific or technological context of the problem being solved. The papers collected here were presented and discussed at a Workshop held at Carnegie-Mellon University, September 29 through October 1, 1991. There are five ma­ jor articles, each with two discussion pieces and a reply. These articles were invited by us following a public solicitation of abstracts. The problems they address are diverse, but all bear on policy decision-making. Though not part of our original design for the Workshop, that commonality of theme does emphasize the usefulness of Bayesian meth­ ods in this arena. Along with the invited papers were several additional commentaries of a general nature; the first comment was invited and the remainder grew out of the discussion at the Workshop. In addition there are nine contributed papers, selected from the thirty-four presented at the Workshop, on a variety of applications. This collection of case studies illustrates the ways in which Bayesian methods are being incorporated into statistical practice. The strengths (and limitations) of the approach become apparent through the examples.

Case Studies in Bayesian Statistics: Volume IV (Lecture Notes in Statistics #140)

The 4th Workshop on Case Studies in Bayesian Statistics was held at the Car­ negie Mellon University campus on September 27-28, 1997. As in the past, the workshop featured both invited and contributed case studies. The former were presented and discussed in detail while the latter were presented in poster format. This volume contains the four invited case studies with the accompanying discus­ sion as well as nine contributed papers selected by a refereeing process. While most of the case studies in the volume come from biomedical research the reader will also find studies in environmental science and marketing research. INVITED PAPERS In Modeling Customer Survey Data, Linda A. Clark, William S. Cleveland, Lorraine Denby, and Chuanhai LiD use hierarchical modeling with time series components in for customer value analysis (CVA) data from Lucent Technologies. The data were derived from surveys of customers of the company and its competi­ tors, designed to assess relative performance on a spectrum of issues including product and service quality and pricing. The model provides a full description of the CVA data, with random location and scale effects for survey respondents and longitudinal company effects for each attribute. In addition to assessing the performance of specific companies, the model allows the empirical exploration of the conceptual basis of consumer value analysis. The authors place special em­ phasis on graphical displays for this complex, multivariate set of data and include a wealth of such plots in the paper.

Case Studies in Bayesian Statistics: Volume V (Lecture Notes in Statistics #162)

The 5th Workshop on Case Studies in Bayesian Statistics was held at the Carnegie Mellon University campus on September 24-25, 1999. As in the past, the workshop featured both invited and contributed case studies. The former were presented and discussed in detail while the latter were presented in poster format. This volume contains the three invited case studies with the accompanying discussion as well as ten contributed pa­ pers selected by a refereeing process. The majority of case studies in the volume come from biomedical research. However, the reader will also find studies in education and public policy, environmental pollution, agricul­ ture, and robotics. INVITED PAPERS The three invited cases studies at the workshop discuss problems in ed­ ucational policy, clinical trials design, and environmental epidemiology, respectively. 1. In School Choice in NY City: A Bayesian Analysis ofan Imperfect Randomized Experiment J. Barnard, C. Frangakis, J. Hill, and D. Rubin report on the analysis of the data from a randomized study conducted to evaluate the New YorkSchool Choice Scholarship Pro­ gram. The focus ofthe paper is on Bayesian methods for addressing the analytic challenges posed by extensive non-compliance among study participants and substantial levels of missing data. 2. In Adaptive Bayesian Designs for Dose-Ranging Drug Trials D. Berry, P. Mueller, A. Grieve, M. Smith, T. Parke, R. Blazek, N.

Case Studies in Bayesian Statistics: Volume VI (Lecture Notes in Statistics #167)

This volume contains invited case studies with the accompanying discussion as well as contributed papers selected by a refereeing process of 6th Workshop on Case Studies in Bayesian Statistics was held at the Carnegie Mellon University in October, 2001.

Case Studies in Bayesian Statistics, Volume II (Lecture Notes in Statistics #105)

Like its predecessor, this second volume presents detailed applications of Bayesian statistical analysis, each of which emphasizes the scientific context of the problems it attempts to solve. The emphasis of this volume is on biomedical applications. These papers were presented at a workshop at Carnegie-Mellon University in 1993.

Case Studies in Data Analysis (Lecture Notes in Statistics #94)

This volume is a collection of eight Case Studies in Data Analysis that appeared in various issues of the Canadian Journal of Statistics (OS) over a twelve­ year period from 1982 to 1993. One follow-up article to Case Study No.4 is also included in the volume. The OS's Section on Case Studies in Data Analysis was initiated by a former editor who wanted to increase the analytical content of the journal. We were asked to become Section Co-Editors and to develop a format for the case studies. Each case study presents analyses of a real data set by two or more analysts or teams of analysts working independently in a simulated consulting context. The section aimed at demonstrating the process of statistical analysis and the possible diversity of approaches and conclusions. For each case study, the Co-Editors found a set of real Canadian data, posed what they thought was an interesting statistical problem, and recruited analysts working in Canada who were willing to tackle it. The published case studies describe the data and the problem, and present and discuss the analysts' solutions. For some case studies, the providers of the data were invited to contribute their own analysis.

Case Studies in Environmental Statistics (Lecture Notes in Statistics #132)

This book offers a set of case studies exemplifying the broad range of statis­ tical science used in environmental studies and application. The case studies can be used for graduate courses in environmental statistics, as a resource for courses in statistics using genuine examples to illustrate statistical methodol­ ogy and theory, and for courses in environmental science. Not only are these studies valuable for teaching about an essential cross-disciplinary activity but they can also be used to spur new research along directions exposed in these examples. The studies reported here resulted from a program of research carried on by the National Institute of Statistical Sciences (NISS) during the years 1992- 1996. NISS was created in 1991 as an initiative of the national statistics or­ ganizations, with the mission to renew and focus efforts of statistical science on important cross-disciplinary problems. One of NISS' first projects was a cooperative research effort with the U.S. Environmental Protection Agency (EPA) on problems of great interest to environmental science and regulation, surely one of today's most important cross-disciplinary activities. With the support and encouragement of Gary Foley, Director of the (then) U.S. EPA Atmospheric Research and Exposure Assessment Laboratory, a project and a research team were assembled by NISS that pursued a program which produced a set of results and products from which this book was drawn.

Case Studies in Reliability and Maintenance (Wiley Series in Probability and Statistics #480)

Introducing a groundbreaking companion book to a bestselling reliability text Reliability is one of the most important characteristics defining the quality of a product or system, both for the manufacturer and the purchaser. One achieves high reliability through careful monitoring of design, materials and other input, production, quality assurance efforts, ongoing maintenance, and a variety of related decisions and activities. All of these factors must be considered in determining the costs of production, purchase, and ownership of a product. Case Studies in Reliability and Maintenance serves as a valuable addition to the current literature on the subject of reliability by bridging the gap between theory and application. Conceived during the preparation of the editors' earlier work, Reliability: Modeling, Prediction, and Optimization (Wiley, 2000), this new volume features twenty-six actual case studies written by top experts in their fields, each illustrating exactly how reliability models are applied. A valuable companion book to Reliability: Modeling, Prediction, and Optimization, or any other textbook on the subject, the book features: * Case studies from fields such as aerospace, automotive, mining, electronics, power plants, dikes, computer software, weapons, photocopiers, industrial furnaces, granite building cladding, chemistry, and aircraft engines * A logical organization according to the life cycle of a product or system * A unified format of discussion enhanced by tools, techniques, and models for drawing one's own conclusions * Pertinent exercises for reinforcement of ideas Of equal value to both students of reliability theory as well as professionals in industry, Case Studies in Reliability and Maintenance should be required reading for anyone seeking to understand how reliability and maintenance issues can be addressed and resolved in the real world.