Advances in Case-Based Reasoning


Book Description

This book constitutes the refereed proceedings of the 9th European Conference on Case-Based Reasoning, ECCBR 2008, held in Trier, Germany, in September 2008. The 34 revised research papers and 5 revised application papers presented together with 3 invited talks were carefully reviewed and selected from 71 submissions. All current issues in case-based reasoning are addressed, ranging from theoretical and methodological issues to advanced applications in various fields such as knowledge discovery, similarity, context-awareness, uncertainty, and health sciences.




Advances in Case-Based Reasoning


Book Description

The papers collected in this volume were presented at the 6th European C- ference on Case-Based Reasoning (ECCBR 2002) held at The Robert Gordon University in Aberdeen, UK. This conference followed a series of very succe- ful well-established biennial European workshops held in Trento, Italy (2000), Dublin, Ireland (1998), Lausanne, Switzerland (1996), and Paris, France (1994), after the initial workshop in Kaiserslautern, Germany (1993). These meetings have a history of attracting ?rst-class European and international researchers and practitioners in the years interleaving with the biennial international co- terpart ICCBR; the 4th ICCBR Conference was held in Vancouver, Canada in 2001. Proceedings of ECCBR and ICCBR conferences are traditionally published by Springer-Verlag in their LNAI series. Case-Based Reasoning (CBR) is an AI problem-solving approach where pr- lems are solved by retrieving and reusing solutions from similar, previously solved problems, and possibly revising the retrieved solution to re?ect di?erences - tween the new and retrieved problems. Case knowledge stores the previously solved problems and is the main knowledge source of a CBR system. A main focus of CBR research is the representation, acquisition and maintenance of case knowledge. Recently other knowledge sources have been recognized as important: indexing, similarity and adaptation knowledge. Signi?cant knowledge engine- ing e?ort may be needed for these, and so the representation, acquisition and maintenance of CBR knowledge more generally have become important.




Advances in Case-Based Reasoning


Book Description

This book constitutes the refereed proceedings of the 7th European Conference on Case-Based Reasoning, ECCBR 2004, held in Madrid, Spain in August/September 2004. The 56 revised full papers presented together with an invited paper and the abstract of an invited talk were carefully reviewed and selected from 85 submissions. All current issues in case-based reasoning, ranging from theoretical and methodological issues to advanced applications in various fields are addressed.




Advances in Case-Based Reasoning


Book Description

This book constitutes the refereed proceedings of the 5th European Workshop on Case-Based Reasonning, EWCBR 2000, held in Trento, Italy in September 2000. The 40 revised full papers presented together with two invited contributions were carefully reviewed and selected for inclusion in the book. All curves issues in case-based reasoning, ranging from foundational and theoretical aspects to advanced applications in various fields are addressed.




Advances in Case-Based Reasoning


Book Description

This book constitutes the refereed proceedings of the 4th European Workshop on Case-Based Reasoning, EWCBR-98, held in Dublin, Ireland, in September 1998. The 41 revised full papers presented were carefully selected and reviewed for inclusion in the proceedings. The contributions address the representation and organization of cases in case-bases, the assessment of case similarity, the efficient retrieval of cases from large case-bases, the adaptation of similar case solutions to fit the current problem, case learning and case-base maintenance, and the application of CBR technology to real-world problems.




Advances in Case-Based Reasoning


Book Description

This book constitutes the refereed proceedings of the 8th European Conference on Case-Based Reasoning, ECCBR 2004, held in Fethiye, Turkey in September 2006. The book presents 31 revised full papers and 5 revised application papers together with 2 invited papers and 2 abstracts of invited talks. The coverage represents snapshot of current current issues in case-based reasoning, ranging from theoretical and methodological issues to advanced applications in various fields.




Advances in Case-Based Reasoning


Book Description

This book constitutes the refereed proceedings of the Third European Workshop on Case-Based Reasoning, EWCBR-96, held in Lausanne, Switzerland, in November 1996. Case-based reasoning is an appealing technique for dealing with the knowledge acquisition bottleneck in computer applications; solutions to new problems are found by adapting similar experience from the past, called cases. The 38 revised full papers presented were carefully selected from a broad variety of submissions after a thorough refereeing process. The volume refleats the state of the art in case-based reasoning research and applications.




Advances in Case-Based Reasoning


Book Description

The type of material considered for publication includes drafts of original papers or monographs, technical reports of high quality and broad interest, advanced-level lectures, reports of meetings, provided they are of exceptional interest and focused on a single topic.




Case-Based Reasoning


Book Description

This book presents case-based reasoning in a systematic approach with two goals: to present rigorous and formally valid structures for precise case-based reasoning, and to demonstrate the range of techniques, methods, and tools available for many applications.




Case-Based Learning


Book Description

Case-based reasoning means reasoning based on remembering previous experiences. A reasoner using old experiences (cases) might use those cases to suggest solutions to problems, to point out potential problems with a solution being computed, to interpret a new situation and make predictions about what might happen, or to create arguments justifying some conclusion. A case-based reasoner solves new problems by remembering old situations and adapting their solutions. It interprets new situations by remembering old similar situations and comparing and contrasting the new one to old ones to see where it fits best. Case-based reasoning combines reasoning with learning. It spans the whole reasoning cycle. A situation is experienced. Old situations are used to understand it. Old situations are used to solve a problem (if there is one to be solved). Then the new situation is inserted into memory alongside the cases it used for reasoning, to be used another time. The key to this reasoning method, then, is remembering. Remembering has two parts: integrating cases or experiences into memory when they happen and recalling them in appropriate situations later on. The case-based reasoning community calls this related set of issues the indexing problem. In broad terms, it means finding in memory the experience closest to a new situation. In narrower terms, it can be described as a two-part problem: assigning indexes or labels to experiences when they are put into memory that describe the situations to which they are applicable, so that they can be recalled later; and at recall time, elaborating the new situation in enough detail so that the indexes it would have if it were in the memory are identified. Case-Based Learning is an edited volume of original research comprising invited contributions by leading workers. This work has also been published as a special issues of MACHINE LEARNING, Volume 10, No. 3.