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[null,"1.","Record Nr.",null,"UNISALENTO991001955199707536"]
[null,null,"Autore",null,"Bertrand, Joseph"]
[null,null,"Titolo",null,"Trattato di algebra elementare / di Giuseppe Bertrand ; prima trad. italiana con note ed aggiunte di Enrico Betti"]
[null,null,"Pubbl/distr/stampa",null,"Firenze : successori Le Monnier, 1899"]
[null,null,"Edizione",null,"[Nuova ed.]"]
[null,null,"Descrizione fisica",null,"vii, 531 p. ; 18 cm"]
[null,null,"Classificazione",null,"AMS 08-01"]
[null,null,"Disciplina",null,"512"]
[null,null,"Soggetti",null,"Algebra"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Translation of: Algèbre"]
[{"$nulls":4},"Ex Libris Mario Lombardo"]
[null,"2.","Record Nr.",null,"UNINA9910768452203321"]
[null,null,"Titolo",null,"Advances in case-based reasoning : 6th European conference, ECCBR 2002, Aberdeen, Scotland, UK, September 4-7, 2002, proceedings / / edited by Susan Craw, Alun Preece"]
[null,null,"Pubbl/distr/stampa",null,"Berlin, Germany ; ; New York, New York : , : Springer, , [2002]"]
[{"$nulls":4},"©2002"]
[null,null,"ISBN",null,"3-540-46119-1"]
[null,null,"Edizione",null,"[1st ed. 2002.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XII, 656 p.)"]
[null,null,"Collana",null,"Lecture Notes in Artificial Intelligence ; ; 2416"]
[null,null,"Disciplina",null,"006.33"]
[null,null,"Soggetti",null,"Expert systems (Computer science)"]
[{"$nulls":4},"Case-based reasoning"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Bibliographic Level Mode of Issuance: Monograph"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Invited Papers -- Integrating Background Knowledge into Nearest-Neighbor Text Classification -- Applying Knowledge Management: Techniques for Building Organisational Memories -- Research Papers -- On the Complexity of Plan Adaptation by Derivational Analogy in a Universal Classical Planning Framework -- Inductive Learning for Case-Based Diagnosis with Multiple Faults -- Diverse Product Recommendations Using an Expressive Language for Case Retrieval -- Digital Image Similarity for Geo-spatial Knowledge Management -- Poetry Generation in COLIBRI -- Adaptation Using Iterated Estimations -- The Use of a Uniform Declarative Model in 3D Visualisation for Case-Based Reasoning -- Experiments on Case-Based Retrieval of Software Designs -- Exploiting Taxonomic and Causal Relations in Conversational Case Retrieval -- Bayesian Case Reconstruction -- Relations between Customer Requirements, Performance Measures, and General Case Properties for Case Base Maintenance -- Representing Temporal Knowledge for Case-Based Prediction -- Local Predictions for Case-Based Plan Recognition -- Automatically Selecting Strategies for Multi-Case-Base Reasoning -- Diversity-Conscious Retrieval -- Improving Case Representation and Case Base Maintenance in Recommender Agents -- Similarity Assessment for Generalizied Cases by Optimization Methods -- Case Acquisition in a Project Planning Environment -- Improving Case-Based Recommendation -- Efficient Similarity Determination and Case Construction Techniques for Case-"]
[{"$nulls":4},"Based Reasoning -- Constructive Adaptation -- A Fuzzy Case Retrieval Approach Based on SQL for Implementing Electronic Catalogs -- Integrating Hybrid Rule-Based with Case-Based Reasoning -- Search and Adaptation in a Fuzzy Object Oriented Case Base -- Deleting and Building Sort Out Techniques for Case Base Maintenance -- Entropy-Based vs. Similarity-Influenced: Attribute Selection Methods for Dialogs Tested on Different Electronic Commerce Domains -- Category-Based Filtering and User Stereotype Cases to Reduce the Latency Problem in Recommender Systems -- Defining Similarity Measures: Top-Down vs. Bottom-Up -- Learning to Adapt for Case-Based Design -- An Approach to Aggregating Ensembles of Lazy Learners That Supports Explanation -- An Experimental Study of Increasing Diversity for Case-Based Diagnosis -- Application Papers -- Collaborative Case-Based Recommender Systems -- Tuning Production Processes through a Case Based Reasoning Approach -- An Application of Case-Based Reasoning to the Adaptive Management of Wireless Networks -- A Case-Based Personal Travel Assistant for Elaborating User Requirements and Assessing Offers -- An Automated Hybrid CBR System for Forecasting -- Using CBR for Automation of Software Design Patterns -- A New Approach to Solution Adaptation and Its Application for Design Purposes -- InfoFrax: CBR in Fused Cast Refractory Manufacture -- Comparison-Based Recommendation -- Case-Based Reasoning for Estuarine Model Design -- Similarity Guided Learning of the Case Description and Improvement of the System Performance in an Image Classification System -- ITR: A Case-Based Travel Advisory System -- Supporting Electronic Design Reuse by Integrating Quality-Criteria into CBR-Based IP Selection -- Building a Case-Based Decision Support System for Land Development Control Using Land Use Function Pattern."]
[null,null,null,"Sommario/riassunto","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."]