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During development of information system, we have problems to choose appropriate architecture, technologies and methods. The conception of information system, designing methods, problems, related with information system development is given in this work. There are mentioned the main security requirement for hospital information system. We analyze created system “Information system of psychophysiology rehabilitation patients”. There are mentioned the main cases why client/server architecture, new technology adaptation were selected. The comparison of methods for data interface realization: PL/SQL language written in stored procedures and query generation is given. The selected method rating - how it speed system developing and how it influence system performance are evaluated. There are given experiments, which decrease system performance by selected methods.

This dissertation presents a novel methodology based on test summaries, which characterize desired tests as constraints written in a mixed imperative and declarative notation, for automated systematic testing of relational applications, such as relational database engines. The methodology has at its basis two novel techniques for effective and efficient testing: (1) mixed-constraint solving, which provides systematic generation of inputs characterized by mixed-constraints using translations among different data domains; and (2) clustered test execution, which optimizes execution of test suites by leveraging similarities in execution traces of different tests using abstract-level undo operations, which allow common segments of partial traces to be executed only once and the execution results to be shared across those tests. A prototype embodiment of the methodology enables a novel approach for systematic testing of commonly used database engines, where test summaries describe (1) input SQL queries, (2) input database tables, and (3) expected output of query execution. An experimental evaluation using the prototype demonstrates its efficacy in systematic testing of relational applications, including Oracle 11g, and finding bugs in them. / text

Semantika informacinių technologijų kontekste yra duomenų apdorojimas pagal prasmę ir kontekstą. Tam įgyvendinti yra taikomas natūralios kalbos apdorojimas, pritaikytas informacijos paieškai, išrinkimui, analizavimui.Taikant semantines technologijas, kūrėjams dažnai kyla klausimas, kaip sukurti semantinės paieškos sąsają, kad ji būtų patogi ir duotų kuo tikslesnius atsakymus į vartotojų užklausas. Šiame darbe aprašomas sukurtas metodas, kuris padeda vartotojui palaipsniui formuoti SPARQL užklausą iš atskirų elementų, dinamiškai keičiant vartotojo sąsają. / Increasing popularity of Semantic Web raises a question how we could make a simple user interface for building semantic queries while keeping high precision of results returned. This thesis presents a method that helps users to create SPARQL queries by allowing to dynamically add components to user interface. The goal of the work is to improve of user interface model for semantic queries by allowing users to construct and change it dynamically till obtaining the desirable answer results. That model was created on the base of analysis of Semantic Web languages, tools and existing portals, their functions and user interfaces. Algorithms for dynamic user interface generation based on user actions were developed that allow creating queries of various complexities with minimal amount of user interface components. Implementation and testing the prototype of the system using movie and wine ontologies has shown that dynamic construction and generation of query interface has desirable functionality and is easily applicable to various ontologies. Experimental comparison with existing semantic search portals has shown that the proposed dynamic user interface generation method could improve precision and recall of semantic queries and may be applied in semantic search portal applications.

Patent documents are important intellectual resources of protecting interests of individuals, organizations and companies. These patent documents have great research values, beneficial to the industry, business, law, and policy-making communities. Patent mining aims at assisting patent analysts in investigating, processing, and analyzing patent documents, which has attracted increasing interest in academia and industry. However, despite recent advances in patent mining, several critical issues in current patent mining systems have not been well explored in previous studies. These issues include: 1) the query retrieval problem that assists patent analysts finding all relevant patent documents for a given patent application; 2) the patent documents comparative summarization problem that facilitates patent analysts in quickly reviewing any given patent documents pairs; and 3) the key patent documents discovery problem that helps patent analysts to quickly grasp the linkage between different technologies in order to better understand the technical trend from a collection of patent documents. This dissertation follows the stream of research that covers the aforementioned issues of existing patent analysis and mining systems. In this work, we delve into three interleaved aspects of patent mining techniques, including (1) PatSearch, a framework of automatically generating the search query from a given patent application and retrieving relevant patents to user; (2) PatCom, a framework for investigating the relationship in terms of commonality and difference between patent documents pairs, and (3) PatDom, a framework for integrating multiple types of patent information to identify important patents from a large volume of patent documents. In summary, the increasing amount and textual complexity of patent repository lead to a series of challenges that are not well addressed in the current generation systems. My work proposed reasonable solutions to these challenges and provided insights on how to address these challenges using a simple yet effective integrated patent mining framework.

En la actualidad, el uso de las tecnologías ha sido primordial para el avance de las sociedades, estas han permitido que personas sin conocimientos informáticos o usuarios llamados “no expertos” se interesen en su uso, razón por la cual los investigadores científicos se han visto en la necesidad de producir estudios que permitan la adaptación de sistemas, a la problemática existente dentro del ámbito informático. Una necesidad recurrente de todo usuario de un sistema es la gestión de la información, la cual se puede administrar por medio de una base de datos y lenguaje específico, como lo es el SQL (Structured Query Language), pero esto obliga al usuario sin conocimientos a acudir a un especialista para su diseño y construcción, lo cual se ve reflejado en costos y métodos complejos, entonces se plantea una pregunta ¿qué hacer cuando los proyectos son pequeñas y los recursos y procesos son limitados? Teniendo como base la investigación realizada por la universidad de Washington[39], donde sintetizan sentencias SQL a partir de ejemplos de entrada y salida, se pretende con esta memoria automatizar el proceso y aplicar una técnica diferente de aprendizaje, para lo cual utiliza una aproximación evolucionista, donde la aplicación de un algoritmo genético adaptado origina sentencias SQL válidas que responden a las condiciones establecidas por los ejemplos de entrada y salida dados por el usuario. Se obtuvo como resultado de la aproximación, una herramienta denominada EvoSQL que fue validada en este estudio. Sobre los 28 ejercicios empleados por la investigación [39], 23 de los cuales se obtuvieron resultados perfectos y 5 ejercicios sin éxito, esto representa un 82.1% de efectividad. Esta efectividad es superior en un 10.7% al establecido por la herramienta desarrollada en [39] SQLSynthesizer y 75% más alto que la herramienta siguiente más próxima Query by Output QBO[31]. El promedio obtenido en la ejecución de cada ejercicio fue de 3 minutos y 11 segundos, este tiempo es superior al establecido por SQLSynthesizer; sin embargo, en la medida un algoritmo genético supone la existencia de fases que amplían los rangos de tiempos, por lo cual el tiempo obtenido es aceptable con relación a las aplicaciones de este tipo. En conclusión y según lo anteriormente expuesto, se obtuvo una herramienta automática con una aproximación evolucionista, con buenos resultados y un proceso simple para el usuario “no experto”. / Actuellement l'usage des technologies est primordial pour l'avance de la société, celles-ci ont permis que des personnes sans connaissances informatiques ou des utilisateurs appelés "non expert" s'intéressent à son usage. C'est la raison pour laquelle les enquêteurs scientifiques se sont vus dans la nécessité de produire les études qui permettent l'adaptation des systèmes à la problématique existante à l'intérieur du domaine informatique. Une nécessité récurrente pour tout utilisateur d'un système est la gestion de l'information, que l’on peut administrer au moyen d'une base de données et de langage spécifique pour celles-ci comme est le SQL (Structured Query Language), mais qui oblige à l'utilisateur à chercher un spécialiste pour sa conception et sa construction, et qui représente des prix et des méthodes complexes. Une question se pose alors, quoi faire quand les projets sont petites et les ressources et les processus limités ? Ayant pour base la recherche de l'université de Washington [39], ce mémoire automatise le processus et applique une différente technique d'apprentissage qui utilise une approche évolutionniste, où l'application d'un algorithme génétique adapté génère des requêtes SQL valides répondant aux conditions établies par les exemples d'entrée et de sortie donnés par l'utilisateur. On a obtenu comme résultat de l’approche un outil dénommé EvoSQL qui a été validé dans cette étude. Sur les 28 exercices employés par la recherche [39], 23 exercices ont été obtenus avec des résultats parfaits et 5 exercices sans succès, ce qui représente 82.1 % d'effectivité. Cette effectivité est supérieure de 10.7 % à celle établie par l'outil développé dans [32] SQLSynthesizer et 75% plus haute que l'outil suivant le plus proche Query by Output QBO [31]. La moyenne obtenue dans l'exécution de chaque exercice a été de 3 min et 11sec, ce qui est supérieur au temps établi par SQlSynthesizer, cependant dans la mesure où un algorithme génétique suppose que l'existence de phases augmente les rangs des temps, le temps obtenu est acceptable par rapport aux applications de ce type. Dans une conclusion et selon ce qui a été antérieurement exposé nous avons obtenu un outil automatique, avec une approche évolutionniste, avec de bons résultats et un processus simple pour l'utilisateur « non expert ». / At present the use of the technologies is basic for the advance of the society; these have allowed that persons without knowledge or so called "non expert" users are interested in this use, is for it that the researchers have seen the need to produce studies that allow the adjustment of the systems the existing at the problematic inside the area of the technology. A need of every user of a system is the management of the information, which can be manage by a database and specific language for these as the SQL (Structured Query Language), which forces the user to come to a specialist for the design and construction of this one, which represents costs and complex methods, but what to do when they are small investigations where the resources and processes are limited? Taking as a base the research of the university of Washington [32], this report automates the process and applies a different learning technique, for which uses an evolutionary approach, where the application of a genetic adapted algorithm generates query SQL valid that answer to the conditions established by the given examples of entry and exit given by the user. There was obtained as a result of the approach a tool named EvoSQL that was validated in the same 28 exercises used by the investigation [32], of which 23 exercises were obtained by ideal results and 5 not successful exercises, which represents 82.1 % of efficiency, superior in 10.7 % to the established one for the tool developed in [32] SQLSynthesizer and 75% higher than the following near tool Query by Output QBO [26]. The average obtained in the execution of every exercise was of 3 min and 11seg that is superior to the time established by SQlSynthesizer, Nevertheless, being a genetic algorithm where the steps existence makes that the ranges of times are extended, the obtained one is acceptable with relation to the applications of this type. In conclusion et according to previously exposed, we have obtained an automatic tool, with an evolutionary approach, with good results and a simple process for the « not expert » user.