Thesis (doctoral)--Universität Kaiserslautern, 2002. / Includes bibliographical references (p. 219-234) and index.

<p>This thesis describes one promising approach where a problem of time<br />series analysis and prediction was solved by using Case Based Reasoning<br />(CBR) technology. Foundations and main concepts of this technology are<br />described in detail. Furthermore, a detailed study of different approaches in<br />time series analysis is given. System CuBaGe (Curve Base Generator) - A<br />robust and general architecture for curve representation and indexing time<br />series databases, based on Case based reasoning technology, was<br />developed. Also, a corresponding similarity measure was modelled for a<br />given kind of curve representation. The presented architecture may be<br />employed equally well not only in conventional time series (where all<br />values are known), but also in some non-standard time series (sparse,<br />vague, non-equidistant). Dealing with the non-standard time series is the<br />highest advantage of the presented architecture.</p> / <p>U ovoj doktorskoj disertaciji prikazan je interesantan i perspektivan pristup<br />re&scaron;avanja problema analize i predviđanja vremenskih serija kori&scaron;ćenjem<br />Case Based Reasoning (CBR) tehnologije. Detaljno su opisane osnove i<br />glavni koncepti ove tehnologije. Takođe, data je komparativna analiza<br />različitih pristupa u analizi vremenskih serija sa posebnim osvrtom na<br />predviđanje. Kao najveći doprinos ove disertacije, prikazan je sistem<br />CuBaGe (Curve Base Generator) u kome je realizovan originalni način<br />reprezentacije vremenskih serija zajedno sa, takođe originalnom,<br />odgovarajućom merom sličnosti. Robusnost i generalnost sistema<br />ilustrovana je realnom primenom u domenu finansijskog predviđanja, gde<br />je pokazano da sistem jednako dobro funkcioni&scaron;e sa standardnim, ali i sa<br />nekim nestandardnim vremenskim serijama (neodređenim, retkim i<br />neekvidistantnim).</p>

Knowledge and knowledge work are key factors of today’s successful companies. This study devises an approach for increasing the performance of knowledge work by shifting it towards a process orientation. Business process management and workflow management are methods for structured and predefined work but are not flexible enough to support knowledge work in a comprehensive way. Case-based reasoning (CBR) uses the knowledge of previously experienced cases in order to propose a solution to a problem. CBR can be used to retrieve, reuse, revise, retain and store functional and process knowledge. The aim of the research was to develop an approach that combines CBR and process execution to improve knowledge work. The research goals are: a casedescription for knowledge work that can be integrated into a process execution system and that contains both functional and process knowledge; a similarity algorithm for the retrieval of functional and procedural knowledge; and an adaptation mechanism that deals with the different granularities of solution parts. This thesis contains a profound literature framework and follows a design science research (DSR) strategy. During the awareness phase of the design science research process, an application scenario was acquired using the case study research method, which is the admission process for a study programme at a university. This application scenario is used to introduce and showcase the combined CBR and process execution approach called ICEBERG-PE, which consists of a case model and CBR services. The approach is implemented as a prototype and can be instantiated using the ICEBERG-PE procedure model, a specific procedure model for ontology-based, CBR projects. The ICEBERG-PE prototype has been evaluated using triangulated evaluation data and different evaluation settings to confirm that the approach is transferable to other contexts. Finally, this thesis concludes with potential recommendations for future research. / Computing / D. Phil. (Information Systems)

No description available.

Schack är ett spel som ofta används för att undersöka olika tekniker inom artificiell intelligens (AI). I det här arbetet ställs frågan om det går att utveckla en AI-agent vars beslutsfattande är baserat på tekniken Case-based Reasoning (CBR) med grundlig likhet som spelar bättre med fallbaser baserade på bättre experter. En AI-agent har utvecklats som spelat ett antal partier mot sig själv med olika fallbaser baserade på olika experter. Efter att ha undersökt resultatet visade de sig att AI-agenten spelar så dåligt att den nästan aldrig lyckades vinna oavsett fallbas, vilket gjorde att det inte gick att rangordna dem efter skicklighet. I framtida arbete är det intressant att undersöka andra likheter än grundlig likhet. Det är även av intresse att undersöka om en CBR-baserad schackspelande AI-agent kan spela schack med hög skicklighet.

The project introduces and subsequently proposes a novel framework, based on the medical model of diagnosis, to facilitate business students' preparation of case analysis. The project also shows students how to apply the framework in a sample case study.

This thesis is about symptom-based troubleshooting of heavy vehicles. The existing troubleshooting system at Scania is adapted to handle errors based on electronic fault codes. This means that some faults, such as mechanical faults when sensors are missing, are difficult to troubleshoot. In the thesis, a method is developed that will be a part of a symptom-based troubleshooting system which can handle all types of errors. The main objectives of the thesis are both to develop a method that can link customer symptoms with system reactions and also to develop formats for both customer symptoms and FMEA for the developed method. In the thesis, a literature study was first conducted in which troubleshooting methods and principles for the formalization of customer data were identified. The identified troubleshooting methods were Bayesian Network, Case-Based-Reasoning and Fault tree analysis. A case study was then conducted which was based on several documents for troubleshooting in gas engines and gas tanks. In the case study, data from the literature study and the empirically collected data were used to develop the final concept of the method. The case study included, among other things, semi-structured interviews to map out the existing troubleshooting process, and a workshop to choose the final concept. In order to meet the objectives of the thesis two research questions and one question linked to the case study were formulated: Research Questions: • RQ1: How is the troubleshooting process affected by the methods that can be used to link customer symptoms with system reactions in heavy vehicles? • RQ2: How can customer data and FMEA be formalized in order to be useful in the troubleshooting process of heavy vehicles? Case Study: • What kind of data is missing from Scania’s existing documentation to link customer symptoms with system reactions? The thesis resulted in a method based on two troubleshooting methods Bayesian network and Case-Based-Reasoning. The method links customer symptoms with system reactions by excluding human considerations and instead relying on previously documented cases and probabilities. A requirement for using this method is a cooperation between customer support, mechanics and development engineers. The formalization of customer symptoms in the developed method is based on what good data is for mechanics in troubleshooting contexts and what customers are capable of communicating; deviation – the customer’s description of the vehicle’s unexpected condition, position – where the customer considers the deviation to be present, context – what happened before, during and after the deviation was discovered. The conclusions that can be drawn is that it is not necessary to link customer symptoms with system reactions since the developed method allows the customer symptoms to be linked directly to the corrective actions needed. In addition, it was noted that the existing documentation at Scania on customer symptoms and system reactions is insufficient. However, this is not problematic as it was shown that FMEA is redundant for the method developed. In order for customer data to be useful, the formalization should include deviation, position and context. Further conclusions are that the role of the customer support becomes less critical when data driven troubleshooting methods are used, and that the accuracy of the developed method will improve over time as more data will be collected. / Detta arbete behandlar symptombaserad felsökning av tunga fordon. Scanias befintliga felsökningssystem är anpassat för att hantera fel som grundas i elektroniska felkoder. Detta innebär att vissa typer av fel, såsom mekaniska fel när sensorer saknas, är svåra att felsöka. I detta arbete utvecklas en metod som ska ingå i ett symptombaserat felsökningssystem eftersom ett sådant system kan hantera alla typer av fel. Målen med arbetet är att utveckla en metod som kan sammankoppla kundsymptom med systemreaktioner, och utveckla format för kundsymptom och FMEA för den framtagna metoden. I arbetet utfördes först en litteraturstudie där felsökningsmetoder och principer för formaliseringen av kunddata identifierades. Felsökningsmetoderna som identifierades var Bayesiska nätvkerk, Case-Based-Reasoning och Felträdsanalys. Därefter utfördes en fallstudie som grundades på underlag om felsökning inom gasmotorer och gastankar. I fallstudien användes data från litteraturstudien och den empiriskt insamlade data för att utveckla det slutgiltiga konceptet. I fallstudien utfördes bland annat semistrukturerade intervjuer för att kartlägga den befintliga felsökningsprocessen, och en workshop för att kunna välja det slutgiltiga konceptet. För att kunna uppfylla arbetets mål formulerades två forskningsfrågor och en frågeställning kopplad till fallstudien: Forskningsfrågor: • F1: Hur påverkas felsökningsprocessen utifrån de metoder som kan användas för att sammankoppla kundsymptom med systemreaktioner inom tunga fordon? • F2: Hur kan kunddata och FMEA formaliseras för att vara användbara inom felsökningsprocessen av tunga fordon? Fallstudie: • Vilken data saknas i Scanias befintliga dokumentation för att kunna sammankoppla kundsymptom med systemreaktioner? Arbetet resulterade i en metod som baseras på de två felsökningsmetoderna Bayesiska nätverk och Case-Based-Reasoning. Metoden sammankopplar kundsymptom med systemreaktioner genom att exkludera mänskligt avvägande och istället förlita sig på tidigare dokumenterade fall och sannolikhet. En förutsättning för att metoden ska kunna användas är ett samarbete mellan kundmottagare, mekaniker och utvecklingsingenjörer. Formaliseringen av kundsymptom i den framtagna metoden bygger på vad bra data är för mekaniker i felsökningssammanhang och vad kunderna är kapabla att förmedla; avvikelse – kundens beskrivning av fordonets oväntade tillstånd, position – var anser kunden att avvikelsen förekommer, kontext – vad hände innan, under och efter att avvikelsen upptäcktes. Slutsatserna som kan dras utifrån arbetet är att det inte är nödvändigt att sammankoppla kundsymptom med systemreaktioner, utan kundsymptom kan sammankopplas direkt med åtgärder med den framtagna metoden. Dessutom noterades det att den befintliga dokumentationen hos Scania angående kundsymptom och systemreaktioner är bristfällig. Detta är inte problematiskt då det påvisades att FMEA inte är nödvändig för att metoden ska fungera. För att kunddata ska vara användbart bör formaliseringen ske med avvikelse, position och kontext. Ytterligare slutsatser är att kundmottagarrollen blir mindre kritisk när datadrivna felsökningsmetoder används, och att den framtagna metodens träffsäkerhet kommer att förbättras över tid allt eftersom mer data har samlats in.

published_or_final_version / Urban Planning and Environmental Management / Doctoral / Doctor of Philosophy

Diagrams are increasingly used in many design methods, and are being taught in a variety of contexts in higher education such as database conceptual design or software design in computer science. They are an important part of many assessments. Currently computer aided assessments are widely used for multiple choice questions. They lack the ability to assess a student's knowledge in a more comprehensive way, which is required for diagram-type student work. The aim of this research is to develop a semi-automatic assessment framework, which enables the use of computer to support the assessment process of diagrammatic solutions, with the focus of ensuring the consistency of grades and feedback on solutions. A novel trace model, that captures design traces of student solutions, was developed as a part of the framework and was used to provide the matching criteria for grouping the solutions. A new marking style, partial marking, was developed to mark these solution groups manually. The Case-Based Reasoning method is utilised in the framework to mark some of the groups automatically. A guideline for scenario writing was proposed to increase the efficiency of automatic marking. A prototype diagram editor, a marking tool and scenario writing environment were implemented for the proposed framework in order to demonstrate proof of concept. The results of experiments show that the framework is feasible to use in the formative assessment and it provides consistent marking and personalised feedback to the students. The framework also has the potential to significantly reduce the time and effort required by the examiner to mark student diagrams. Although the constructed framework was specifically used for the assessment of database diagrams, the framework is generic enough to be used for other types of graph-based diagram.

Cette thèse propose deux approches pour améliorer la qualité des réponses d'un système de raisonnement à partir de cas (RàPC) utilisant des connaissances produites par une communauté en ligne. La première approche concerne la mise en œuvre d'un modèle permettant de gérer la fiabilité des connaissances produites par la communauté sous la forme d'un score. Ce score de fiabilité est utilisé d'une part pour filtrer les connaissances non fiables afin qu'elles ne soient pas utilisées par le système de RàPC et d'autre part pour classer les réponses retournées par le système. La deuxième approche concerne la représentation de la typicalité entre sous-classes et classes dans une organisation hiérarchique. La typicalité est alors utilisée pour réorganiser les connaissances hiérarchiques utilisées par le système de RàPC. L'apport de ces deux approches a été évalué dans le cadre de eTaaable, un système de RàPC qui adapte des recettes de cuisine en utilisant des connaissances produites par une communauté en ligne. L'évaluation montre que la gestion de la fiabilité des connaissances produites par la communauté améliore la qualité des réponses retournées par eTaaable. De même, l'évaluation montre que l'utilisation par eTaaable des hiérarchies des connaissances réorganisées en exploitant la typicalité améliore également la qualité des réponses / This research work presents two approaches to improve the quality of the results returned by a case-based reasoning system (CBR) exploiting knowledge produced by an e-community. The first approach relies on a new model to manage the trustworthiness of the knowledge produced by the e community. In this model, the trustworthiness is represented through a score which is used to filter untrustworthy knowledge so that the CBR system will not use it anymore. Moreover, the trustworthiness score is also used to rank the CBR results. The second approach addresses the issue of representing the typicality between subclasses and classes in a hierarchy. The typicality is used to change the hierarchical organization used by the CBR system. Both approaches have been evaluated in the framework of eTaaable, a CBR system which adapts cooking recipes using knowledge coming from an e-community. The evaluations show that managing the trustworthiness of the knowledge produced by an e-community improves the quality of the results returned by eTaaable. The evaluations also shows that eTaaable returns also better results when using knowledge reorganized according to typicality.