National Repository of Grey Literature 23 records found  1 - 10nextend  jump to record: Search took 0.00 seconds. 
Modelling and Management of Multi-Model Data
Koupil, Pavel ; Holubová, Irena (advisor) ; Klettke, Meike (referee) ; Krátký, Michal (referee)
Title: Modelling and Management of Multi-Model Data Author: Pavel Koupil (Čontoš) Department: Department of Software Engineering Supervisor: doc. RNDr. Irena Holubová, Ph.D., Department of Software Engi- neering Abstract: With the advent of multi-model database management systems, the boundaries of many approaches to data processing were pushed. The aspect of multi-model data introduces a new dimension of complexity and new chal- lenges not seen in single-model systems. We have to address issues arising from the combination of interconnected and often contradictory logical models, such as, e.g., order-preserving/-ignorant, aggregate-oriented/-ignorant, schema-full/- less/-mixed approaches, intra- and inter-model references, intra- and inter-model integrity constraints, or full and partial intra- and inter-model data redundancy. Hence, a number of mature and verified approaches for various data manage- ment tasks commonly used for single-model DBMSs cannot be directly applied to multi-model DBMSs. This thesis aims to propose a new family of unified approaches for both conceptual and logical multi-model modelling and data management. We first analyse the state-of-the-art of related areas. Then we propose abstract data structures to represent multi-model schema and data. These structures are then utilised...
Recommender systems - models, methods, experiments
Peška, Ladislav ; Vojtáš, Peter (advisor) ; Jannach, Dietmar (referee) ; Krátký, Michal (referee)
This thesis investigates the area of preference learning and recommender systems. We concentrated recommending on small e-commerce vendors and efficient usage of implicit feedback. In contrast to the most published studies, we focused on investigating multiple diverse implicit indicators of user preference and substantial part of the thesis aims on defining implicit feedback, models of its combination and aggregation and also algorithms employing them in preference learning and recommending tasks. Furthermore, a part of the thesis focuses on other challenges of deploying recommender systems on small e-commerce vendors such as which recommending algorithms should be used or how to employ third party data in order to improve recommendations. The proposed models, methods and algorithms were evaluated in both off-line and on-line experiments on real world datasets and on real e-commerce vendors respectively. Datasets are included to the thesis for the sake of validation and further research. Powered by TCPDF (www.tcpdf.org)
Evolution and Adaptability of Complex Applications
Polák, Marek ; Holubová, Irena (advisor) ; Rahayu, Wenny (referee) ; Krátký, Michal (referee)
Evolution and Adaptability of Complex Applica- tions Abstract In these days the applications become more complex that causes maintenance problems while evolving these applications. A change in one part of the appli- cation can significantly affect other parts of the application. The next aspect can be related systems which communicate with this application. They must be updated to satisfy their functionality. These problems can concern multiple do- mains, e.g., UML diagrams, XML schema diagrams, relational schemas, etc. We focus on this problem from the perspective of the MDA, which uses the platform independent model (PIM) for a general view of the problem and the platform specific model (PSM) for particular domains. Moreover, these models can be in- terconnected. We propose novel PSM models from various widely used domains, operations over these models and algorithms for model transformations. Thanks to the MDA principle, it is possible to combine presented models and model a complex application. All models and related algorithms we present were experi- mentally implemented and tested in the DaemonX framework on real-word data for their verification. 1
Conceptual Modeling for XML
Nečaský, Martin ; Pokorný, Jaroslav (advisor) ; Krátký, Michal (referee) ; Thalheim, Bernhardt (referee)
XML is a popular format for data representation. As the amount of data represented in XML grows, it is necessary to concentrate on the process of modeling XML schemes of the XML representations. However, modeling the XML schemes on the level f XML schema languages, such as XML Schema, has some drawbacks. A natural idea to improve this situation is to model the XML schemes rst on the conceptual level. It is motivated by the world of relational databases where we also start modeling the data fi rst on the conceptual level. In this thesis we focus on conceptual modeling for XML. We start with a motivating example to point out to several problems that can arise when using only XML schema languages for modeling XML schemes. We discuss how modeling the data rst on the conceptual level can help. We also show that conceptual modeling for XML has some speci cs that should be taken into account by a conceptual model for XML. Mainly, we show that it is necessary to separate the conceptual modeling process to two parts. First, we need to model the data independently of its representation in XML. Second, we need to model how the data is represented in di erent types of XML documents. In the next step, we analyze in detail existing approaches to conceptual modeling for XML and show their limitations. In the main part of...
Bulk Evaluation of User-Defined Functions in XQuery
Bednárek, David ; Král, Jaroslav (advisor) ; Kuznetsov, Sergey (referee) ; Krátký, Michal (referee)
XPath queries are usually translated into an algebra that combines traditional relational operators and XML-speciffic ones. In particular, FLWOR loops are represented using nest, unnest, join, and similar operators and their original nested-loop nature disappears, creating an opportunity for bulk evaluation and join reordering. In XQuery, two additional issues shall be handled - tree construction and the presence of user-deffined functions. The recursive nature of functions pushes the problem outside of the range of relational algebra. This thesis presents a novel evaluation framework based on an expanding network of relational operators, called R-program. In this environment, functions are evaluated in bulk instead of evaluating each call separately. Besides obvious advantages of bulk evaluation, R-programs also allow rearrangement of data flow across function boundaries. A set of program transformations employing these capabilities is described; together with rule-based static interprocedural analysis algorithms used to determine the applicability of the transformations.
Analysis of Real-World Data and Their Exploitation
Stárka, Jakub ; Holubová, Irena (advisor) ; Krátký, Michal (referee) ; Collard, Martine (referee)
Title: Analyses of Real-World Data and Their Exploitation Author: Mgr. Jakub Stárka Department: Department of Software Engineering Supervisor: RNDr. Irena Holubová, Ph.D. Abstract: The typical optimization strategy of many data processing techniques is ex- ploitation of the knowledge of constructs typically used in real-world applications. However, such approach requires a repeatable, updatable and detailed analysis of a rep- resentative data set. Having such a requirement a number of related problems arises, such as automatic crawling of the data, data extraction, schema inference, and efficient performance of analyses over a huge data volume as well as exploitation of the results in current applications. In this thesis we describe a complex framework for performing statistical analyses of real-world documents and we propose characteristics that appropriately capture and describe features of XML documents, RDF triples and XQuery queries. Additionally we provide experimental results over a few selected real-world data sets. Last but not least we introduce an easily extensible tool that enables one to implement, test and compare new modules of the XML schema inference process. We describe not only the framework, but the area of schema inference in general, including related work and open problems. Keywords:...
Evolution and Adaptability of Complex Applications
Polák, Marek ; Holubová, Irena (advisor) ; Rahayu, Wenny (referee) ; Krátký, Michal (referee)
Evolution and Adaptability of Complex Applications Abstract In these days the applications become more complex that causes maintenance problems while evolving these applications. A change in one part of the applica- tion can significantly affect other parts of the application. The next aspect can be related systems which communicate with this application. They must be up- dated to satisfy their correct functionality. These problems can concern multiple domains, e.g., UML diagrams, XML schema diagrams, relational schemas, APIs, etc. We focus on this problem from the perspective of the MDA, which uses the platform independent model (PIM) for a general view of the problem and the platform specific model (PSM) for particular domains. Moreover, these models can be interconnected and related to each other. We propose novel PSM models from various widely used domains, operations over these models and algorithms for model transformations. Thanks to the MDA principle, it is possible to combine presented models and model a complex application. All models and related algorithms we present were experimentally implemented and tested in the DaemonX framework on real-world data for their verification. 1
Evolution and Adaptability of Complex Applications
Polák, Marek ; Holubová, Irena (advisor) ; Rahayu, Wenny (referee) ; Krátký, Michal (referee)
Evolution and Adaptability of Complex Applica- tions Abstract In these days the applications become more complex that causes maintenance problems while evolving these applications. A change in one part of the appli- cation can significantly affect other parts of the application. The next aspect can be related systems which communicate with this application. They must be updated to satisfy their functionality. These problems can concern multiple do- mains, e.g., UML diagrams, XML schema diagrams, relational schemas, etc. We focus on this problem from the perspective of the MDA, which uses the platform independent model (PIM) for a general view of the problem and the platform specific model (PSM) for particular domains. Moreover, these models can be in- terconnected. We propose novel PSM models from various widely used domains, operations over these models and algorithms for model transformations. Thanks to the MDA principle, it is possible to combine presented models and model a complex application. All models and related algorithms we present were experi- mentally implemented and tested in the DaemonX framework on real-word data for their verification. 1

National Repository of Grey Literature : 23 records found   1 - 10nextend  jump to record:
See also: similar author names
1 Krátký, Marek
8 Krátký, Martin
2 Krátký, Matouš
10 Krátký, Michal
1 Krátký, Milan
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