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Case-based reasoning approach to adaptive web-based educational systems

Alves, Paulo; Amaral, Luís; Pires, José Adriano
Fonte: IEEE Publicador: IEEE
Tipo: Conferência ou Objeto de Conferência
Português
Relevância na Pesquisa
96%
Virtual learning environments systems are based on the classroom paradigm, in which the knowledge is transmitted for all the students in the same way. To enhance e-learning, adapting the contents to the needs of each student is essential, and a more personalized learning support is required. The adoption of pedagogical agents and new artificial intelligence methodologies can response to the needs of individual students and provide a more effective collaboration in virtual learning environments. The learning experience of each student can be adapted to others students with the same characteristics. The adaptation of past cases to solve new problems is one of the features of case-based reasoning methodology, which can provide an effective knowledge transmission, based on learning activities. In this paper, we present a case-based reasoning approach to Adaptive Web-based Educational Systems using fuzzy logic to adapt e-learning contents and contexts according to the student learning style and individual needs.

Composing music with case-based reasoning

Pereira, Francisco; Grilo, Carlos; Macedo, Luís; Cardoso, Amílcar
Fonte: Universidade de Coimbra Publicador: Universidade de Coimbra
Tipo: Conferência ou Objeto de Conferência
Português
Relevância na Pesquisa
95.92%
Music is one of the most intriguing and joyful domain of research and analysis. Driven by this insatiable curiosity, Musical Analysis has emerged to formally understand and structure music and its intrinsic intention and causality. Each complete analysis of a piece points to issues that go far beyond the normal graphical music representation. A better analysis is important not only to a better interpretation, but also to a more perfect composition. An exceptional composer is indeed an exceptional analyst. This paper presents a computational approach to music composition through the use and exploration of musical analysis. Centered on Case-Based Reasoning and Planning techniques, it consists on creating new solutions by keeping, transforming and extrapolating knowledge from already expert-made music analysis. For our approach, each analysis is represented as a precisely structured Case, divisible into all of its components. The process of composition we adopt is progressive, left-to-right, and top-to-bottom and has some similarities with (Wallas’ 1926) theory for creative production (Macedo et al. 1996a) which we adapted for this specifically structured and complex domain. The resulting implemented program has already generated several different musical pieces...

Composing music with case-based reasoning

Pereira, Francisco C.; Grilo, Carlos Fernando Almeida; Macedo, Luís; Cardoso, Fernando Amílcar Bandeira
Fonte: Instituto Politécnico de Leiria Publicador: Instituto Politécnico de Leiria
Tipo: Conferência ou Objeto de Conferência
Publicado em //1997 Português
Relevância na Pesquisa
95.92%
Comunicação apresentada na International Conference on Computational Models of Creative Cognition, Dublin, 1997.; Music is one of the most intriguing and joyful domain of research and analysis. Driven by this insatiable curiosity, Musical Analysis has emerged to formally understand and structure music and its intrinsic intention and causality. Each complete analysis of a piece points to issues that go far beyond the normal graphical music representation. A better analysis is important not only to a better interpretation, but also to a more perfect composition. An exceptional composer is indeed an exceptional analyst. This paper presents a computational approach to music composition through the use and exploration of musical analysis. Centered on Case-Based Reasoning and Planning techniques, it consists on creating new solutions by keeping, transforming and extrapolating knowledge from already expert-made music analysis. For our approach, each analysis is represented as a precisely structured Case, divisible into all of its components. The process of composition we adopt is progressive, left-to-right, and top-to-bottom and has some similarities with (Wallas’ 1926) theory for creative production (Macedo et al. 1996a) which we adapted for this specifically structured and complex domain. The resulting implemented program has already generated several different musical pieces...

A hybrid case adaptation approach for case-based reasoning

POLICASTRO, Claudio A.; CARVALHO, Andre C. P. L. F.; DELBEM, Alexandre C. B.
Fonte: SPRINGER Publicador: SPRINGER
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
96.03%
Case-Based Reasoning is a methodology for problem solving based on past experiences. This methodology tries to solve a new problem by retrieving and adapting previously known solutions of similar problems. However, retrieved solutions, in general, require adaptations in order to be applied to new contexts. One of the major challenges in Case-Based Reasoning is the development of an efficient methodology for case adaptation. The most widely used form of adaptation employs hand coded adaptation rules, which demands a significant knowledge acquisition and engineering effort. An alternative to overcome the difficulties associated with the acquisition of knowledge for case adaptation has been the use of hybrid approaches and automatic learning algorithms for the acquisition of the knowledge used for the adaptation. We investigate the use of hybrid approaches for case adaptation employing Machine Learning algorithms. The approaches investigated how to automatically learn adaptation knowledge from a case base and apply it to adapt retrieved solutions. In order to verify the potential of the proposed approaches, they are experimentally compared with individual Machine Learning techniques. The results obtained indicate the potential of these approaches as an efficient approach for acquiring case adaptation knowledge. They show that the combination of Instance-Based Learning and Inductive Learning paradigms and the use of a data set of adaptation patterns yield adaptations of the retrieved solutions with high predictive accuracy.

Sistematização da assistência de enfermagem usando raciocínio baseado em casos implementado em JAVA.; Nursing assistance systematization using case-based reasoning implemented in JAVA.

Mendes, Marcio Almeida
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 26/11/2009 Português
Relevância na Pesquisa
95.99%
Mesmo com a evolução tecnológica em vários setores, a área de enfermagem tem tido investimentos escassos em pesquisa e desenvolvimento capazes de atender suas expectativas, principalmente no campo da inteligência artificial. As expectativas dos enfermeiros convergem à melhora de seus processos clínicos que resultará em uma maior aproximação de seus pacientes. Além disso, há dificuldade em reunir diagnósticos de enfermagem nos hospitais, onde diversos registros clínicos e procedimentos preenchidos manualmente e armazenados ainda em folhas de papel. Esta condição compromete a legibilidade dos documentos envolvidos nos processos hospitalares, e seu arquivamento torna o processo de levantamento de informações moroso, o que acaba por inviabilizar a pesquisa à qual poderia resultar em informações importantes para melhora do processo de tomada de decisões. O objetivo desta dissertação foi trazer o estado da arte em inteligência artificial focado em raciocínio baseado em casos e sua aplicação na sistematização da assistência de enfermagem. No sentido de validar o modelo levantado foi criado um protótipo para apresentar uma aplicação que pudesse auxiliar os enfermeiros em seus processos clínicos, armazenando suas experiências em uma base de casos para futuras pesquisas. O protótipo consistiu em digitalizar diagnósticos de enfermagem pediátrica...

Raciocínio baseado em casos aplicado ao gerenciamento de falhas em redes de computadores; Case-based reasoning applied to fault management in computer networks

Melchiors, Cristina
Fonte: Universidade Federal do Rio Grande do Sul Publicador: Universidade Federal do Rio Grande do Sul
Tipo: Dissertação Formato: application/pdf
Português
Relevância na Pesquisa
96.03%
Com o crescimento do número e da heterogeneidade dos equipamentos presentes nas atuais redes de computadores, o gerenciamento eficaz destes recursos toma-se crítico. Esta atividade exige dos gerentes de redes a disponibilidade de uma grande quantidade de informações sobre os seus equipamentos, as tecnologias envolvidas e os problemas associados a elas. Sistemas de registro de problemas (trouble ticket systems) tem lido utilizados para armazenar os incidentes ocorridos, servindo como uma memória histórica da rede e acumulando o conhecimento derivado do processo de diagnose e resolução de problemas. Todavia, o crescente número de registros armazenados torna a busca manual nestes sistemas por situações similares ocorridas anteriormente muito morosa e imprecisa. Assim, uma solução apropriada para consolidar a memória histórica das redes é o desenvolvimento de um sistema especialista que utilize o conhecimento armazenado nos sistemas de registro de problemas para propor soluções para um problema corrente. Uma abordagem da Inteligência Artificial que tem atraído enorme atenção nos últimos anos e que pode ser utilizada para tal fim é o raciocínio baseado em casos (casebased reasoning). Este paradigma de raciocínio visa propor soluções para novos problemas através da recuperação de um caso similar ocorrido no passado...

Case based reasoning versus artificial neural networks in medical diagnosis

Alves, Victor; Novais, Paulo; Nelas, Luís; Maia, Moreira; Ribeiro, Victor
Fonte: Universidade do Minho Publicador: Universidade do Minho
Tipo: Conferência ou Objeto de Conferência
Publicado em //2003 Português
Relevância na Pesquisa
95.9%
Embedding Machine Learning technology into Intelligent Diagnosis Systems adds a new potential to such systems and in particular to the imagiology ones. In our work, this is achieved using the data acquired from MEDsys, a computational environment that supports medical diagnosis systems that use an amalgam of knowledge discovery and data mining techniques, which use the potential of an extension to the language of Logic Programming, with the functionalities of a connectionist approach to problem solving using Artificial Neural Networks. One’s goal aims to conceive an alternative method to detect medical pathologies, as an alternative to the one in use in the actual medical diagnostic system; i.e., Case Based Reasoning versus Artificial Neural Networks. A comparative study of these two approaches to machine learning will be presented, taking into account its applicability in MEDsys.

Using case-based reasoning to support alternative dispute resolution

Carneiro, Davide; Novais, Paulo; Andrade, Francisco Carneiro Pacheco; Zeleznikow, John; Neves, José
Fonte: Springer Publicador: Springer
Tipo: Conferência ou Objeto de Conferência
Publicado em //2010 Português
Relevância na Pesquisa
95.9%
Springer - Series Advances in Intelligent and Soft Computing, vol. 79; Recent trends in communication technologies led to a shift in the already traditional Alternative Dispute Resolution paradigm, giving birth to the Online Dispute Resolution one. In this new paradigm, technologies are used as a way to deliver better, faster and cheaper alternatives to litigation in court. However, the role that technology plays can be even further enhanced through the use of artefacts from the Artificial Intelligence field. In this paper we present UMCourt, an Online Dispute Resolution tool that borrows concepts from the fields of Law and Artificial Intelligence. The system keeps the parties informed about the possible consequences of their litigation if their problems are to be settled in court. Moreover, it makes use of a Case-based Reasoning algorithm that searches for solutions for the litigation considering past known similar cases, as a way to enhance the negotiation process. When parties have access to all this information and are aware of the consequences of their choices, they can take better decisions that encompass all the important aspects of a litigation process.; The work described in this paper is included in TIARAC - Telematics and Artificial Intelligence in Alternative Conflict Resolution Project (PTDC/JUR/71354/2006)...

From real-world regulations to concrete norms for software agents : a case-based reasoning approach

Balke, Tina; Novais, Paulo; Andrade, Francisco Carneiro Pacheco; Eymann, Torsten
Fonte: CEUR Publicador: CEUR
Tipo: Conferência ou Objeto de Conferência
Publicado em //2009 Português
Relevância na Pesquisa
95.9%
When trying to use software agents (SAs) for real-world business and thereby putting them in a situation to operate under real-world laws, the abstractness of human regulations often poses severe problems. Thus, human regulations are written in a very abstract way, making them open to a wide range of interpretations and applicable for several scenarios as well as stable over a longer period of time. However, in order to be applicable for SAs, regulations need to be precise and unambiguous. This paper presents a case-based reasoning approach in order to bridge the gap between abstract human regulations and the concrete regulations needed for SAs, by developing and using a knowledge base that can be used for drawing analogies and thereby serves as reference for ranslating" abstract terms in human regulations.

Handling default data under a case-based reasoning approach

Fernandes, Bruno; Freitas, Mauro; Analide, Cesar; Vicente, Henrique; Neves, José
Fonte: SciTePress Publicador: SciTePress
Tipo: Conferência ou Objeto de Conferência
Publicado em /01/2015 Português
Relevância na Pesquisa
95.96%
The knowledge acquired through past experiences is of the most importance when humans or machines try to find solutions for new problems based on past ones, which makes the core of any Case-based Reasoning approach to problem solving. On the other hand, existent CBR systems are neither complete nor adaptable to specific domains. Indeed, the effort to adapt either the reasoning process or the knowledge representation mechanism to a new problem is too high, i.e., it is extremely difficult to adapt the input to the computational framework in order to get a solution to a particular problem. This is the drawback that is addressed in this work.; This work is funded by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within projects PEst-OE/EEI/UI0752/2014 and PEst-OE/QUI/UI0619/2012.

Handling Default Data under a Case-Based Reasoning Approach

Fernandes, Bruno; Freitas, Mauro; Analide, César; Vicente, Henrique; Neves, José
Fonte: Scitepress – Science and Technology Publications Publicador: Scitepress – Science and Technology Publications
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
95.96%
The knowledge acquired through past experiences is of the most importance when humans or machines try to find solutions for new problems based on past ones, which makes the core of any Case-based Reasoning approach to problem solving. On the other hand, existent CBR systems are neither complete nor adaptable to specific domains. Indeed, the effort to adapt either the reasoning process or the knowledge representation mechanism to a new problem is too high, i.e., it is extremely difficult to adapt the input to the computational framework in order to get a solution to a particular problem. This is the drawback that is addressed in this work.

Case-based reasoning - An effective paradigm for providing diagnostic support for stroke patients

Baig, Mariam
Fonte: Quens University Publicador: Quens University
Tipo: Tese de Doutorado Formato: 4912478 bytes; application/pdf
Português
Relevância na Pesquisa
95.92%
A Stroke can affect different parts of the human body depending on the area of brain effected; our research focuses on upper limb motor dysfunction for stroke patients. In current practice, ordinal scale systems are used for conducting physical assessment of upper limb impairment. The reliability of these assessments is questionable, since their coarse ratings cannot reliably distinguish between the different levels of performance. This thesis describes the design, implementation and evaluation of a novel system to facilitate stroke diagnosis which relies on data collected with an innovative KINARM robotic tool. This robotic tool allows for an objective quantification of motor function and performance assessment for stroke patients. The main methodology for the research is Case Based Reasoning (CBR) - an effective paradigm of artificial intelligence that relies on the principle that a new problem is solved by observing similar, previously encountered problems and adapting their known solutions. A CBR system was designed and implemented for a repository of stroke subjects who had an explicit diagnosis and prognosis. For a new stroke patient, whose diagnosis was yet to be confirmed and who had an indefinite prognosis, the CBR model was effectively used to retrieve analogous cases of previous stroke patients. These similar cases provide useful information to the clinicians...

Case-based reasoning for meta-heuristics self-parameterization in a multi-agent scheduling system

Pereira, Ivo; Madureira, Ana Maria; Moura, Paulo Oliveira
Fonte: Instituto Politécnico do Porto Publicador: Instituto Politécnico do Porto
Tipo: Conferência ou Objeto de Conferência
Publicado em //2011 Português
Relevância na Pesquisa
95.93%
A novel agent-based approach to Meta-Heuristics self-configuration is proposed in this work. Meta-heuristics are examples of algorithms where parameters need to be set up as efficient as possible in order to unsure its performance. This paper presents a learning module for self-parameterization of Meta-heuristics (MHs) in a Multi-Agent System (MAS) for resolution of scheduling problems. The learning is based on Case-based Reasoning (CBR) and two different integration approaches are proposed. A computational study is made for comparing the two CBR integration perspectives. In the end, some conclusions are reached and future work outlined.

Uso da metodologia de raciocínio baseado em casos na investigação de irregularidades nas internações hospitalares; Using case-based reasoning to search problems in hospital admission authorization

Lorenzi, Fabiana
Fonte: Universidade Federal do Rio Grande do Sul Publicador: Universidade Federal do Rio Grande do Sul
Tipo: Dissertação Formato: application/pdf
Português
Relevância na Pesquisa
95.93%
Raciocínio Baseado em Casos (RBC) a uma técnica de Inteligência Artificial para representação de conhecimento e inferência, que propõe a solução de novos problemas adaptando soluções que foram usadas para resolver problemas anteriores. A descrição de problemas existentes, conhecida como casos, é utilizada para sugerir um meio de resolver um novo problema, avisar o usuário de possíveis falhas observadas no passado e para interpretar a situação atual. Esta dissertação tem por objetivos apresentar um estudo sobre o use de RBC, aplicado ao desenvolvimento de um sistema de administração hospitalar. A aplicação escolhida é o controle e avaliação de Autorizações de Interações Hospitalares (AIH's). Atualmente, este controle é realizado manualmente pela Secretaria da Saúde Municipal de Porto Alegre, que tem um prazo de 48 horas para avaliar o faturamento de cada hospital e apontar as irregularidades. Isso é um problema, pois o volume do faturamento é grande para um prazo tão curto e muitas vezes as AIH's com irregularidades podem passar desapercebidas. O sistema considerado deve realizar o controle e avaliação de AIH's dos hospitais de Porto Alegre, e deve ser capaz de detectar irregularidades nãotriviais na cobrança das internações realizadas pelos hospitais conveniados do Sistema Único de Saúde (SUS). O estudo realizado considerou as etapas de aplicação da metodologia de RBC...

Educase – intelligent system for pedagogical advising using case-based reasoning

Moura, Elionai; Cunha, José António; Analide, Cesar
Fonte: World Academy of Science, Engineering and Technology Publicador: World Academy of Science, Engineering and Technology
Tipo: Artigo de Revista Científica
Publicado em /04/2015 Português
Relevância na Pesquisa
95.9%
This paper introduces a proposal scheme for an Intelligent System applied to Pedagogical Advising using Case-Based Reasoning, to find consolidated solutions before used for the new problems, making easier the task of advising students to the pedagogical staff. We do intend, through this work, introduce the motivation behind the choices for this system structure, justifying the development of an incremental and smart web system who learns bests solutions for new cases when it’s used, showing technics and technology.

Playing with cases: Tempo Transformations of Jazz Performances using Case-Based Reasoning

Lopez de Mantaras, Ramon; Grachten, Maarten; Arcos, Josep Ll.
Fonte: AAAI Press Publicador: AAAI Press
Tipo: Comunicación de congreso Formato: 34972 bytes; application/pdf
Português
Relevância na Pesquisa
95.9%
Invited paper at the FLAIRS'07 The original publication is available at www.aaai.org/Press; The research described here focuses on global tempo transformations of monophonic recordings of saxophone jazz performances. We have investigated the problem of how a performance played at a particular tempo can be automatically rendered at another tempo while preserving its expressivity. That is, listeners should not be able to notice, from the expressivity of a performance, that has been scaled up or down from another tempo. To do so, we have developed a case-based reasoning system called TempoExpress. The results we have obtained have been extensively compared against a standard technique called Uniform Time Stretching (UTS), and we show that our approach is superior to UTS.; Peer reviewed

Beyond Individualism: Modeling Team Playing Behavior in Robot Soccer Through Case-Based Reasoning

Ros, Raquel; Veloso, Manuela; López de Mantaras, Ramón; Sierra, Carles; Arcos, Josep Ll.
Fonte: AAAI Press Publicador: AAAI Press
Tipo: Comunicación de congreso Formato: 129043 bytes; application/pdf
Português
Relevância na Pesquisa
95.98%
The original publication is available at www.aaai.org/Press; We propose a Case-Based Reasoning approach for action selection in the robot soccer domain presented in the 8th European Conference on Case-Based Reasoning (2006). Based on the current state of a game, the robots retrieve the most similar past situation and then the team reproduces the sequence of actions performed in that occasion. In this domain we have to deal with all the difficulties that a real environment involves.; Partial funding by the Spanish Ministry of Education and Science project MID-CBR (TIN2006-15140-C03-01) and partly sponsored by BBNT Solutions, LLC under contract nº. FA8760-04-C0002. Raquel Ros holds a scholarship from the Generalitat de Catalunya Government.; Peer reviewed

Emergent Case-Based Reasoning Applications

Lopez de Mantaras, Ramon; Perner, Petra; Cunninghan, Padraig
Fonte: Cambridge University Press Publicador: Cambridge University Press
Tipo: Artículo Formato: 79772 bytes; application/pdf
Português
Relevância na Pesquisa
95.93%
The basic principle underpinning case-based reasoning (CBR) is that new problems can be solved by reusing solutions to past problems. The generality of this idea means that CBR is finding application in a wide variety of areas. The special advantage of CBR is that a case can be a very convenient means of capturing knowledge, especially in weak theory domains where the relationship between causes and effects may not be well understood. Cases may embody more than problem-solving knowledge; the knowledge in a case may be a creative structure or a complex behavior pattern. The widespread applicability of this idea means that it has been exploited in a diverse range of areas across the arts and sciences. This article provides a brief summary of some of these applications.; Peer reviewed

Retrieval, reuse, revision and retention in case-based reasoning

Lopez de Mantaras, Ramon; McSherry, David; Bridge, Derek; Leake, David; Smyth, Barry; Craw, Susan; Faltings, Boi; Maher, Mary L.; Cox, Michael T.; Forbus, Kenneth; Keane, Mark; Aamodt, Agnar; Watson, Ian
Fonte: Cambridge University Press Publicador: Cambridge University Press
Tipo: Artículo Formato: 416540 bytes; application/pdf
Português
Relevância na Pesquisa
95.94%
El original está disponible en www.journals.cambridge.org; Case-based reasoning (CBR) is an approach to problem solving that emphasizes the role of prior experience during future problem solving (i.e., new problems are solved by reusing and if necessary adapting the solutions to similar problems that were solved in the past). It has enjoyed considerable success in a wide variety of problem solving tasks and domains. Following a brief overview of the traditional problem-solving cycle in CBR, we examine the cognitive science foundations of CBR and its relationship to analogical reasoning. We then review a representative selection of CBR research in the past few decades on aspects of retrieval, reuse, revision, and retention.; Peer reviewed

Evolutionary adaptation in case - based reasoning. An application to cross-domain analogies for mediation

Gunes Baydin, Atilim; Puyol-Gruart, Josep
Fonte: [Barcelona] : Universitat Autònoma de Barcelona, Publicador: [Barcelona] : Universitat Autònoma de Barcelona,
Tipo: Tesis i dissertacions electròniques; info:eu-repo/semantics/doctoralThesis; info:eu-repo/semantics/publishedVersion Formato: application/pdf
Publicado em //2014 Português
Relevância na Pesquisa
96.1%
L'analogia juga un papel fonamental en la resolucio de problemes i es troba darrere de molts dels processos centrals de la capacitat cognitiva humana, fins al punt que s'ha considerat "el nucli del coneixement". El raonament analogic funciona a traves del proces de la transferencia, l'us del coneixement apres en una situacio en l'altra per a la qual no va ser destinat. El paradigma de raonament basat en casos (case-based reasoning, CBR) presenta un model molt relacionat, pero lleugerament diferent de raonament utilitzat principalment en la intel.ligencia artificial; diferent en part perque el raonament analogic se centra habitualment en la similitud estructural entre-dominis mentre que CBR te a veure amb la transferencia de solucions entre els casos semanticament similars dins d'un domini especific. En aquesta tesi, ens unim a aquests enfocaments interrelacionats de la ciència cognitiva, la psicologia i la intel.ligencia artificial, en un sistema CBR, on la recuperacio i l'adaptacio es duen a terme per l'Motor d'Associacio Estructural (SME) i son recolzats per el raonament de sentit comu integrant la informacio des de diverses bases de coneixement. Per permetre aixo, utilitzem una estructura de representacio de casos que es basa en les xarxes semantiques. Aixo ens dona un model CBR capac de recuperar i adaptar solucions de dominis que son aparentment diferents pero estructuralment molt similars...