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Auflistung nach Schlagwort "Case-based reasoning"

1 - 5 von 5
  • Zeitschriftenartikel
    Automated Enactment Tracking for Dynamic Workflows
    (KI - Künstliche Intelligenz: Vol. 24, No. 4, 2010) Sauer, Thomas
    The notion of workflows is an established concept to coordinate the activities within an organization. However, human workflow participants typically have to explicitly report the steps taken, limiting acceptance and effectiveness of workflow technology. In the presented PhD thesis, the novel approach of automated enactment tracking is introduced to overcome this problem. Using a Multi-Agent System, the data produced during everyday activities is evaluated in a robust and flexible manner. The system applies Case-Base Reasoning to identify the tasks performed, following the principle that similar tasks produce similar data. Agents further collaborate with each other to identify processes enacted in parallel, and to compensate for missing or inaccurate information.
  • Zeitschriftenartikel
    Integration of Similarity-based and Deductive Reasoning for Knowledge Management
    (KI - Künstliche Intelligenz: Vol. 24, No. 2, 2010) Mougouie, Babak
    Many disciplines in computer science combine similarity-based and logic-based reasoning. The problem is that the disciplines combine these independently of each other. For example in Case-Based Reasoning (CBR) (Aamodt and Plaza, AI Commun. 7(1):39–59, 1994; Bergmann et al., Künstl. Intell. 23(1):5–11, 2009; Bergmann, Experience Management: Foundation, Development, Methodology and Internet-based Applications, LNAI, vol. 2432, Springer, Berlin, 2002), the combination is applied in a sequential manner and not systematically as follows: a set of solutions is retrieved from a case-base using a similarity measure and then deductive reasoning is applied to adapt the retrieved solutions to a query. The aim of this dissertation (Mougouie, Ph.D. thesis, Trier University, Germany, 2009) is to integrate similarity-based and deductive reasoning in a unified manner within the context of Knowledge Management (KM).
  • Zeitschriftenartikel
    Strategic Search Support on Macro and Micro Level
    (Datenbank-Spektrum: Vol. 14, No. 1, 2014) Tacke, Andreas; Kriewel, Sascha
    Consumers increasingly turn to online resources to get access to medical information. Despite their lack of procedural and domain knowledge, users often have complex information needs. Additionally, incomplete or inaccurate information can negatively affect medical decisions. Existing systems only partially address these problems.This work presents a prototypical implementation of a comprehensive support concept. It aims at giving users, in particular lay people searching for medical information, appropriate assistance on both the strategic and the tactical level while they are trying to solve complex search tasks. The article also describes a series of user experiments conducted as part of a master’s thesis and discusses their results.
  • Zeitschriftenartikel
    The RatioLog Project: Rational Extensions of Logical Reasoning
    (KI - Künstliche Intelligenz: Vol. 29, No. 3, 2015) Furbach, Ulrich; Schon, Claudia; Stolzenburg, Frieder; Weis, Karl-Heinz; Wirth, Claus-Peter
    Higher-level cognition includes logical reasoning and the ability of question answering with common sense. The RatioLog project addresses the problem of rational reasoning in deep question answering by methods from automated deduction and cognitive computing. In a first phase, we combine techniques from information retrieval and machine learning to find appropriate answer candidates from the huge amount of text in the German version of the free encyclopedia “Wikipedia”. In a second phase, an automated theorem prover tries to verify the answer candidates on the basis of their logical representations. In a third phase—because the knowledge may be incomplete and inconsistent—we consider extensions of logical reasoning to improve the results. In this context, we work toward the application of techniques from human reasoning: We employ defeasible reasoning to compare the answers w.r.t. specificity, deontic logic, normative reasoning, and model construction. Moreover, we use integrated case-based reasoning and machine learning techniques on the basis of the semantic structure of the questions and answer candidates to learn giving the right answers.
  • Zeitschriftenartikel
    Two-Phased Knowledge Formalisation for Hydrometallurgical Gold Ore Process Recommendation and Validation
    (KI - Künstliche Intelligenz: Vol. 28, No. 4, 2014) Sauer, Christian Severin; Rintala, Lotta; Roth-Berghofer, Thomas
    This paper describes an approach to externalising and formalising expert knowledge involved in the design and evaluation of hydrometallurgical process chains for gold ore treatment. The objective was to create a case-based reasoning application for recommending and validating a treatment process of gold ores. We describe a twofold approach. Formalising human expert knowledge about gold mining situations enables the retrieval of similar mining contexts and respective process chains, based on prospection data gathered from a potential gold mining site. Secondly, empirical knowledge on hydrometallurgical treatments is formalised. This enabled us to evaluate and, where needed, redesign the process chain that was recommended by the first aspect of our approach. The main problems with formalisation of knowledge in the domain of gold ore refinement are the diversity and the amount of parameters used in literature and by experts to describe a mining context. We demonstrate how similarity knowledge was used to formalise literature knowledge. The evaluation of data gathered from experiments with an initial prototype workflow recommender, Auric Adviser, provides promising results.