Search (17 results, page 1 of 1)

  • × language_ss:"e"
  • × theme_ss:"Case Based Reasoning"
  1. Mazzucchelli, A.; Sartori , F.: String similarity in CBR platforms : a preliminary study (2014) 0.01 
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    Abstract
    Case Based Reasoning is a very important research trend in Artificial Intelligence and can be a powerful approach in the solution of complex problems characterized by heterogeneous knowledge. In this paper we present an ongoing research project where CBR is exploited to support the identification of enterprises potentially going to bankruptcy, through a comparison of their balance indexes with the ones of similar and already closed firms. In particular, the paper focuses on how developing similarity measures for strings can be profitably supported by metadata models of case structures and semantic methods like Query Expansion.
    Pages
    S.22-29
    Series
    Communications in computer and information science; 478
  2. Akerele, O.; David, A.; Osofisan, A.: Using the concepts of Case Based Reasoning and Basic Categories for enhancing adaptation to the user's level of knowledge in Decision Support System (2014) 0.01 
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    Abstract
    In most search systems, mapping queries with documents employs techniques such as vector space model, naïve Bayes, Bayesian theorem etc. to classify resulting documents. In this research studies, we are proposing the use of the concept of basic categories to representing the user's level of knowledge based on the concepts he employed during his search activities, so that the system could propose adapted results based on the observed user's level of knowledge. Our hypothesis is that this approach will enhance the decision support system for solving decisional problems in which information retrieval constitutes the backbone technical problem.
    Series
    Advances in knowledge organization; vol. 14
    Source
    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  3. Ram, A.; Santamaria, J.C.: Continuous case-based reasoning (1997) 0.01 
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    Abstract
    Introduces a new method for continuous case-based reasoning, and discusses its applications to the dynamic selection, modification and acquisition of robot bahaviours in an autonomous navigation system, SINS (self-improving navigation system): The computer program and the underlying method are systematically evaluated through statistical analysis of results from several empirical studies. Discusses case-based reasoning issues addressed by this research
    Date
    6. 3.1997 16:22:15
  4. Kohno, T.: Error repair and knowledge acquisition via case-based reasoning (1997) 0.01 
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    Abstract
    Proposes a new architecture combining rule-based reasoning (RBR), case based reasoning (CBR) and knowledge acquisition technology in a system which solves pattern search problems. Details the pattern search problem, the system architecture and functions, error repair method via case-based reasoning, the knowledge acquisition method, system evaluation, and discusses related work
    Date
    6. 3.1997 16:22:15
  5. Löckenhoff, H.: Case-Based Teaching/Learning for issue orientation and control (1996) 0.01 
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    Abstract
    Case Based Reasoning (CBR) is discussed in connection with a wide variety of knowledge aspects. Obviously knowledge acquisition under conditions of rapid and increasingly disruptive change will necessarily rely on the proper use of case experience. The following remarks emerged from practice oriented teaching/learning in the domians of social sciences, practical philosophy, didactics and epistemology. The main interest will be directed to methodical concepts of knowledge transfer, in particular to didactics and learning within the teaching/learning system
    Series
    Fortschritte in der Wissensorganisation; Bd.4
    Source
    Analogie in der Wissensrepräsentation: Case-Based Reasoning und räumliche Modelle. 4. Tagung der deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation, Trier, 17.-20. Oktober 1995. Hrsg.: H. Czap u.a
  6. Golding, A.R.; Rosenbloom, P.S.: Improving accuracy by combining rule-based and case-based reasoning (1996) 0.00 
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    Date
    6. 3.1997 16:22:15
  7. Araj, H.: Integration of an analogical reasoning model in a model of case resolution (1996) 0.00 
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    Abstract
    The resolution of cases in law depends on the generation of metaphors by analogy. It progresses by association, affinity and juxtaposition of two divergent ideas in an integrative approach. To argue a case, a legal expert cannot limit himself to the perception of isolated facts, but instead must find affinities between fields expressing more cohesion in law. In this paper, it is argued that the legal specialist relies on abstract categorization to discover a precedent and thereby create a metaphorical link that serves in the argumentation stage, and also later on in the resolution of the case. On this basis, a model of case reasoning is charted that integrates a model of analogical reasoning
  8. Issues and applications of case-based reasoning in design (1997) 0.00 
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    Footnote
    Rez. in: JASIS 49(1998) no.8, S.762-764 (P.G. Underwood)
  9. He, W.; Erdelez, S.; Wang, F.-K.; Shyu, C.-R.: ¬The effects of conceptual description and search practice on users' mental models and information seeking in a case-based reasoning retrieval system (2008) 0.00 
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    Abstract
    This paper reportes a study that investigated the effects of conceptual description and search practice on users' mental models and information seeking in a case-based reasoning retrieval (CBR) system with a best match search mechanism. This study also found examined how the presence of a mental model affects the users' search performance and satisfaction in this system. The results of this study revealed that the conceptual description and search practice treatments do not have significantly different effects on the types of user's mental models, search correctness, and search satisfaction. However, the search practice group spent significantly less time than the conceptual description group in finding the results. Qualitative analysis for the subjects' post mental models revealed that subjects in the conceptual description group seem to have more complete mental models of the best match system than those in the search practice group. This study also that subjects with the best match mental models have significantly higher search correctness and search result satisfaction than subjects without the best match mental models. However, the best match mental models do not guarantee less search time in finding the results. This study did not find a significant correlation among search time, search correctness and search satisfaction. The study concludes with suggestions for future research and implications for system developers who are interested in CBR retrieval systems.
  10. Dearden, A.M.; Harrison, M.D.: Abstract models for HCI (1997) 0.00 
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    Abstract
    Investigates the use of formal mathematical models in the design of interactive systems and argues for the development of generic models that describe the behaviour of a class of interactive systems. It is possible to construct a generic model of a class of interactive systems at an intermediate level of abstraction. Such a model would offer wider reusability than detailed specifications of a single system, but greater expressiveness and support for software development than fully generate abstract models. Reviews a number of existing models in the literature and presents a generic model of interactive case memories, a class of systems used in case-based reasoning
  11. Tsatsaoulis, C.; Cheng, Q.; Wei, H.-Y.: Integrating case-based reasoning and decision theory (1997) 0.00 
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    Abstract
    Reports on a methodology that lets case-based reasoning use decision-theoretic approaches to deal with unknown proble features and how to make decisions in the presence of these unknowns. Implements the methodology in a case-based design assistant that helps chemists design pharmaceuticals
  12. Mataras, R.L.D.; Plaza, E.: Case-based reasoning : an overview (1997) 0.00 
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    Abstract
    Gives an overview of CBR with emphasis on European ctivites in the field. Identifies major open problems of CBR associated with: retrieval/selection, memory organization, matching, adaptation/evaluation, forgetting and integration with other techniques
  13. Althoff, K.-D.; Wess, S.; Manago, M.; Bergmann, R.; Maurer, F.; Auriol, E.; Conruyt, N.; Traphöner, R.; Bräuer, M.; Dittrich, S.: Induction and case-based reasoning for classification tasks (1994) 0.00 
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    Abstract
    We present 2 techniques for reasoning from cases to solve classification tasks: induction and case-based reasoning. We contrast the 2 technologies (that are often confused) and show how they complement each other. Based on this, we describe how they are integrated in one single platform for reasoning from cases: the INRECA system
    Series
    Studies in classification, data analysis, and knowledge organization
  14. Ress, D.A.; Young, R.E.: ¬A distributed fuzzy constraint satisfaction system with context-based reasoning (1998) 0.00 
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    Abstract
    Presents a fuzzy constraint satisfaction system which can be used in a distributive environment where large problems can be broken down into smaller constraint networks for easier processing. Identifies contexts which exist within the constraint satisfaction system. Context based reasoning is identified both within and among constraint networks. Outlines the motviation behind the research and describes the fuzzy constraint satisfaction system FuzCon. Points out 3 mappings of the context-based reasoning 'ist' operator to fuzzy constraints and presents an example of designing a printed wiring board
    Footnote
    Contribution to a special issue on using context in computer applications
  15. Rissland, E.L.; Daniels, J.J.: ¬The synergistic application of CBR to IR (1996) 0.00 
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    Abstract
    Discusses a hybrid approach combining case-based reasoning and information retrieval for the retrieval of full text documents. It takes as input a standard symbolic representation of a problem case and retrieves text of relevant cases from a document collection dramatically larger than the case base available to the CBR system. It works by performing a standard HYPO style analysis and uses the texts associated with important classes of cases found in this analysis to seed a modified version of INQUERY's relevance feedback mechanism in order to generate a query composed of individual terms or pairs of terms. It exteds the reach of CBR to much larger corpora, and it anbales the injection of knowledge based techniques into traditional IR. Describes the CBR-IR approach and reports on-going experiments
  16. Ozturk, P.; Aamodt, A.: ¬A context model for knowledge-intensive case-based reasoning (1998) 0.00 
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    Footnote
    Contribution to a special issue on using context in computer applications
  17. He, W.; Tian, X.: ¬A longitudinal study of user queries and browsing requests in a case-based reasoning retrieval system (2017) 0.00 
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