289 research outputs found

    A Column Styled Composable Schema Matcher for Semantic Data-types

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    The 4th Conference of PhD Students in Computer Science

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    XSLT Benchmarking

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    Hlavním cílem této práce bylo vytvoření XSLT Benchmarku, tedy srovnání dostupných XSLT procesorů. Nejprve jsme si stanovili hlavní kritéria XSLT procesorů (cena, korektnost, rychlost, využití paměti, podpora, OS a UX), která budeme diskutovat. Poté jsme shrnuli existující XSLT procesory, popsali jednotlivé typy procesorů (program, knihovna a prohlížeč) a ohodnotili kritéria cena, podpora, OS a UX. Abychom mohli ohodnotit kritéria korektnost, rychlost a využití paměti, museli jsme si vytvořit vhodné testovací prostředí. Vytvořený program XSLT Benchmarking je jedním z hlavních přínosů této práce. Součástí programu jsou také připravené testy. Při jejich vytváření, jsme vycházeli z 5787 stažených XSLT souborů. Testy byly vytvořeny na základě analýzy těchto souborů. Zaprvé jsme zkoumali obecné vlastnosti XSLT souborů (použité elementy, použité XSLT verze, formát výstupu atd.). Zadruhé jsme zkoumali zaměření jejich použití. Dalším velkým přínosem této práce je shrnutí výsledků testů z různých pohledů. V tomto shrnutí jsme okomentovali další kritéria a vlastnosti testovaných procesorů. Na závěr jsme shrnuli možná rozšíření našeho programu i naší analýzy.The main goal of this work was to create an XSLT Benchmark, to compare available XSLT processors. At first, we determined main criteria of XSLT processors (price, correctness, speed, memory usage, support, OS and UX), which we discussed. Next, we summarized existing XSLT processors, described individual types of processors (program, library and browser) and measured criteria price, support, OS} and UX. We had to create appropriate test environment to measure criteria correctness, speed and memory usage. Created program XSLT Benchmarking is one of the main benefits of this work. The program also includes tests. We created tests based on 5787 downloaded XSLT files. Tests were created based on the analysis of these files. Firstly, we researched common features of XSLT files (used elements, used XSLT versions, output format etc.). Secondly, we researched focuses of their usages. Next big benefit of this work is a summary of results of tests from different views. We discussed other criteria and features of tested processors. Finally, we summarized possible extensions of our program and also of our analysis.Department of Software EngineeringKatedra softwarového inženýrstvíFaculty of Mathematics and PhysicsMatematicko-fyzikální fakult

    Knowledge engineering for mental-health risk assessment and decision support

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    Mental-health risk assessment practice in the UK is mainly paper-based, with little standardisation in the tools that are used across the Services. The tools that are available tend to rely on minimal sets of items and unsophisticated scoring methods to identify at-risk individuals. This means the reasoning by which an outcome has been determined remains uncertain. Consequently, there is little provision for: including the patient as an active party in the assessment process, identifying underlying causes of risk, and eecting shared decision-making. This thesis develops a tool-chain for the formulation and deployment of a computerised clinical decision support system for mental-health risk assessment. The resultant tool, GRiST, will be based on consensual domain expert knowledge that will be validated as part of the research, and will incorporate a proven psychological model of classication for risk computation. GRiST will have an ambitious remit of being a platform that can be used over the Internet, by both the clinician and the layperson, in multiple settings, and in the assessment of patients with varying demographics. Flexibility will therefore be a guiding principle in the development of the platform, to the extent that GRiST will present an assessment environment that is tailored to the circumstances in which it nds itself. XML and XSLT will be the key technologies that help deliver this exibility

    Linked Open Data - Creating Knowledge Out of Interlinked Data: Results of the LOD2 Project

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    Database Management; Artificial Intelligence (incl. Robotics); Information Systems and Communication Servic
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