Šiuolaikinė mokykla prisitaiko prie vis naujų visuomenės poreikių, tampa atvira besimokančia organizacija, kurioje labai svarbus bendradarbiavimo modelis organizacijos viduje ir organizacijos ryšiai su kitomis įstaigomis. Kaimiškose vietovėse esančios ugdymo įstaigos tenkina bendruomenės narių poreikius, sprendžia socialines, edukologines visuomenės problemas, todėl norint suteikti kvalifikuotą pagalbą bendruomenės nariams, ugdymo įstaigos kuria bendradarbiavimo tinklą, į kurį turi įtraukti viešojo sektoriaus organizacijas. Šiame darbe analizuojamos kaimo mokyklos bendradarbiavimo su viešųjų įstaigų problemos. Daug dėmesio skiriama švietimo organizacijos ryšiams su visuomene taikomoms priemonėms ir jų įtakai ieškant bendradarbiavimo būdų su kitomis organizacijomis. Įvertinama mokyklos bendradarbiavimo kultūros nauda visuomenei. Teorinėje dalyje nagrinėjama švietimo organizacijos bendradarbiavimo problema, bendradarbiavimo samprata, švietimo organizacijos kultūros įtaka mokyklos viduje ir su viešosiomis organizacijomis. Daug dėmesio skiriama švietimo organizacijos ryšiams su visuomene taikomoms priemonėms ir jų įtakai ieškant bendradarbiavimo būdų su kitomis organizacijomis. Praktinėje dalyje analizuojama kaimo mokyklos bendradarbiavimo su viešosiomis ir kitomis organizacijomis situacija. Tiriama, kokie veiksniai lemia švietimo organizacijos bendradarbiavimo kultūros kūrimą ir kas įtakoja organizacijos įvaizdžio formavimą, kuris padeda bendradarbiauti su įvairiomis... [toliau žr. visą tekstą] / Modern school is adapting to new needs of the society, it becomes more open learning organisation, where inside cooperation model of the organisation and its relations with other institutions are very important. Educational institutions that are located in the countryside meet the needs of community members, such institutions solve social and educational problems of the society therefore to provide qualified help to the memebers of society educational institutions create cooperation net (system) which involves public institutions. Problems of cooperation between village school and public entities are analysed in this work. A lot of attention is given to means of communication between the society and educational institution, and their influence on search of ways of communication with other organisations. The use of cooperation of the school is evaluated. The problems of cooperation of educational institution, conception of cooperation, influence of the culture of educational institution inside the school and with public entities are analyzed in the theoretical part of the work. A lot of attention is given to means of communication between the society and the educational institution and their influence on search of ways of communication with other organizations. The situation of cooperation between village school and public entities and other organizations are analysed in the practical part of the work. It is analyzed what factors condition creation of culture of cooperation... [to full text]

This thesis presents novel ideas and research findings for the Web of Data – a global data space spanning many so-called Linked Open Data sources. Linked Open Data adheres to a set of simple principles to allow easy access and reuse for data published on the Web. Linked Open Data is by now an established concept and many (mostly academic) publishers adopted the principles building a powerful web of structured knowledge available to everybody. However, so far, Linked Open Data does not yet play a significant role among common web technologies that currently facilitate a high-standard Web experience. In this work, we thoroughly discuss the state-of-the-art for Linked Open Data and highlight several shortcomings – some of them we tackle in the main part of this work. First, we propose a novel type of data source meta-information, namely the topics of a dataset. This information could be published with dataset descriptions and support a variety of use cases, such as data source exploration and selection. For the topic retrieval, we present an approach coined Annotated Pattern Percolation (APP), which we evaluate with respect to topics extracted from Wikipedia portals. Second, we contribute to entity linking research by presenting an optimization model for joint entity linking, showing its hardness, and proposing three heuristics implemented in the LINked Data Alignment (LINDA) system. Our first solution can exploit multi-core machines, whereas the second and third approach are designed to run in a distributed shared-nothing environment. We discuss and evaluate the properties of our approaches leading to recommendations which algorithm to use in a specific scenario. The distributed algorithms are among the first of their kind, i.e., approaches for joint entity linking in a distributed fashion. Also, we illustrate that we can tackle the entity linking problem on the very large scale with data comprising more than 100 millions of entity representations from very many sources. Finally, we approach a sub-problem of entity linking, namely the alignment of concepts. We again target a method that looks at the data in its entirety and does not neglect existing relations. Also, this concept alignment method shall execute very fast to serve as a preprocessing for further computations. Our approach, called Holistic Concept Matching (HCM), achieves the required speed through grouping the input by comparing so-called knowledge representations. Within the groups, we perform complex similarity computations, relation conclusions, and detect semantic contradictions. The quality of our result is again evaluated on a large and heterogeneous dataset from the real Web. In summary, this work contributes a set of techniques for enhancing the current state of the Web of Data. All approaches have been tested on large and heterogeneous real-world input. / Die vorliegende Arbeit stellt neue Ideen sowie Forschungsergebnisse für das Web of Data vor. Hierbei handelt es sich um ein globales Netz aus sogenannten Linked Open Data (LOD) Quellen. Diese Datenquellen genügen gewissen Prinzipien, um Nutzern einen leichten Zugriff über das Internet und deren Verwendung zu ermöglichen. LOD ist bereits weit verbreitet und es existiert eine Vielzahl von Daten-Veröffentlichungen entsprechend der LOD Prinzipien. Trotz dessen ist LOD bisher kein fester Baustein des Webs des 21. Jahrhunderts. Die folgende Arbeit erläutert den aktuellen Stand der Forschung und Technik für Linked Open Data und identifiziert dessen Schwächen. Einigen Schwachstellen von LOD widmen wir uns in dem darauf folgenden Hauptteil. Zu Beginn stellen wir neuartige Metadaten für Datenquellen vor – die Themen von Datenquellen (engl. Topics). Solche Themen könnten mit Beschreibungen von Datenquellen veröffentlicht werden und eine Reihe von Anwendungsfällen, wie das Auffinden und Explorieren relevanter Daten, unterstützen. Wir diskutieren unseren Ansatz für die Extraktion dieser Metainformationen – die Annotated Pattern Percolation (APP). Experimentelle Ergebnisse werden mit Themen aus Wikipedia Portalen verglichen. Des Weiteren ergänzen wir den Stand der Forschung für das Auffinden verschiedener Repräsentationen eines Reale-Welt-Objektes (engl. Entity Linking). Für jenes Auffinden werden nicht nur lokale Entscheidungen getroffen, sondern es wird die Gesamtheit der Objektbeziehungen genutzt. Wir diskutieren unser Optimierungsmodel, beweisen dessen Schwere und präsentieren drei Ansätze zur Berechnung einer Lösung. Alle Ansätze wurden im LINked Data Alignment (LINDA) System implementiert. Die erste Methode arbeitet auf einer Maschine, kann jedoch Mehrkern-Prozessoren ausnutzen. Die weiteren Ansätze wurden für Rechnercluster ohne gemeinsamen Speicher entwickelt. Wir evaluieren unsere Ergebnisse auf mehr als 100 Millionen Entitäten und erläutern Vor- sowie Nachteile der jeweiligen Ansätze. Im verbleibenden Teil der Arbeit behandeln wir das Linking von Konzepten – ein Teilproblem des Entity Linking. Unser Ansatz, Holistic Concept Matching (HCM), betrachtet abermals die Gesamtheit der Daten. Wir gruppieren die Eingabe um eine geringe Laufzeit bei der Verarbeitung von mehreren Hunderttausenden Konzepten zu erreichen. Innerhalb der Gruppen berechnen wir komplexe Ähnlichkeiten, und spüren semantische Schlussfolgerungen und Widersprüche auf. Die Qualität des Ergebnisses evaluieren wir ebenfalls auf realen Datenmengen. Zusammenfassend trägt diese Arbeit zum aktuellen Stand der Forschung für das Web of Data bei. Alle diskutierten Techniken wurden mit realen, heterogenen und großen Datenmengen getestet.

Santuokos sudarymu sukuriami šeimos teisiniai santykiai: vyras ir moteris įgyja specifinį teisinį statusą – tampa sutuoktiniais, o kartu perima asmenines neturtines ir turtines teises ir pareigas. Sutuoktinius, įgyvendinant turto valdymo, naudojimosi ir disponavimo teises, sieja glaudūs tarpusavio priklausomybės, artimi santykiai, kurie iš esmės sudaro jų teisinių santykių turinį. Santuoką sudariusių asmenų turtinių santykių aiškumas tampa ypač aktualiu klausimu užtikrinant bei apsaugant tiek pačių sutuoktinių, tiek trečiųjų asmenų interesus, kadangi, nesudarius vedybų sutarties, bet koks susituokus įgytas turtas tampa bendrąja jungtine nuosavybe. Sutuoktinių nuosavybės teisės į individualią įmonę , kaip turtinį kompleksą, ją įkūrus po santuokos sudarymo, ir yra šio darbo objektas. Viena kylančių problemų susijusi su neapibrėžtumu, tarpusavyje lyginant Lietuvos Respublikos Civiliniame kodekse ir LR Individualių įmonių įstatyme įtvirtintas normas: remiantis CK formulavimu, santuokos metu įsteigta įmonė priskirtina bendrajai jungtinei nuosavybei, tuo tarpu IĮ įstatyme reglamentuojama, kad IĮ steigėju ir savininku gali būti tik vienas fizinis asmuo, šiuo atveju – vienas iš sutuoktinių. Šio darbo tikslas - išanalizuoti, ar IĮ gali turėti kelis savininkus. / Family relations are established by conjugnality of a man and a woman: they come into position of a husbant and a wife and obtains personal property and non-property rights and interests. Wedded persons are bond by close interdependence ties that make the essence of their legal relations. The clarity of property relations of wedded persons is very important to secure and protect not only their, but also the interests of third parties, i. e. creditors, because in the absence of wedding contract, property acquired during the marriage is automatically presumed to be owned jointly by both spouses. The ownership of a company organized as a sole proprietorship that is established by one of the spouses while being in marriage is the object of this work. The problem of interdetermination arises while seeking to determine the ownership rights of spouses to a SP: Lithuania‘s Civil Code sets the rule that company established during the marriage is presumed to be an object of community property, whereas the Statute of Sole Proprietorships‘ allows a company organized as SP to be owned by a single person, in this instance – one of the spouses. The issue of this work is to analyse if a company organized as SP may have a few owners.

This study is an investigation of the correlation between Grade 9 students’ self-theories of their intelligence and their tendency for intellectual engagement. Individuals have been shown to self-identify, with respect to their self-theories of intelligence as either entity theorists (who think of their own intelligence as fixed and fairly unchangeable), or incremental theorists (who think of their intelligence as malleable and able to be increased over time). Previous research has shown that individuals have a strong tendency to self-select one or the other of these theoretical frameworks. This study examined the correlation of this identification with individuals’ tendency to become intellectually engaged in their learning. Other demographic factors were also explored. A moderate correlation between students’ self-theory of their intelligence and their tendency for intellectual engagement was demonstrated. In this study, female students showed a higher proportion of an incremental self-theory of intelligence than males. Implications for educational leadership and classroom planning and instruction were explored

Off balance sheet financing (OBF) is either not visible or only partially visible in financial reporting for a number of reasons. It has attracted controversy in the light of its employment in a number of major corporate scandals. Previous investigations dominated by short works and consultancy papers have focused mainly on the financial aspects of OBF. This academic cross-country research on the use of OBF in the UK and US capital markets was undertaken to extend the published analyses to include a legal perspective by studying its legal implications for directors, financial advisers, auditors and financial regulators. The study’s legal focus prompted relying primarily on the doctrinal approach, which was in turn completed by the use of a modified case study in order to help address the how and why issues of the research phenomenon. The study found that OBF instruments are double-edge financial instruments with good and bad consequences. When corporations used OBF for liquidity enhancement or to realise financial savings, they result in positive outcomes. In contrast, when used for aggressive window-dressing or in the manipulation of financial reporting for fraudulent ends, OBF mechanisms generated serious legal liabilities for directors, auditors, and financial advisers in terms of compensation suits or even criminal sanctions. Financial regulators were nonetheless found to be less likely to face legal consequences as a result of current judicial attitudes on the tort of public misfeasance. However, the extensive applications of OBF in conjunction with other forms of creative accounting have resulted in various regulatory responses. On a comparative note, litigation and enforcement actions were found to be relatively more extensive in the US because of the higher incidence of large corporate frauds and the work of regulatory champions especially in New York using deferred prosecution agreements.

The study is about the foundation and registration procedures of legal entities. The author compares Lithuanian procedures with the proceduresof various different countries. Also the historical base of foundation procedures in Lithuania are described. The study is finished with detail analysis of different forms of legal entities in Lithuania.

Record linkage refers to the task of finding and linking records (in a single database or in a set of data sources) that refer to the same entity. Automating the record linkage process is a challenging problem, and has been the topic of extensive research for many years. However, the changing nature of the linkage process and the growing size of data sources create new challenges for this task. This thesis studies the record linkage problem for Web data sources. Our hypothesis is that a generic and extensible set of linkage algorithms combined within an easy-to-use framework that integrates and allows tailoring and combining of these algorithms can be used to effectively link large collections of Web data from different domains. To this end, we first present a framework for record linkage over relational data, motivated by the fact that many Web data sources are powered by relational database engines. This framework is based on declarative specification of the linkage requirements by the user and allows linking records in many real-world scenarios. We present algorithms for translation of these requirements to queries that can run over a relational data source, potentially using a semantic knowledge base to enhance the accuracy of link discovery. Effective specification of requirements for linking records across multiple data sources requires understanding the schema of each source, identifying attributes that can be used for linkage, and their corresponding attributes in other sources. Schema or attribute matching is often done with the goal of aligning schemas, so attributes are matched if they play semantically related roles in their schemas. In contrast, we seek to find attributes that can be used to link records between data sources, which we refer to as linkage points. In this thesis, we define the notion of linkage points and present the first linkage point discovery algorithms. We then address the novel problem of how to publish Web data in a way that facilitates record linkage. We hypothesize that careful use of existing, curated Web sources (their data and structure) can guide the creation of conceptual models for semi-structured Web data that in turn facilitate record linkage with these curated sources. Our solution is an end-to-end framework for data transformation and publication, which includes novel algorithms for identification of entity types and their relationships out of semi-structured Web data. A highlight of this thesis is showcasing the application of the proposed algorithms and frameworks in real applications and publishing the results as high-quality data sources on the Web.

Record linkage refers to the task of finding and linking records (in a single database or in a set of data sources) that refer to the same entity. Automating the record linkage process is a challenging problem, and has been the topic of extensive research for many years. However, the changing nature of the linkage process and the growing size of data sources create new challenges for this task. This thesis studies the record linkage problem for Web data sources. Our hypothesis is that a generic and extensible set of linkage algorithms combined within an easy-to-use framework that integrates and allows tailoring and combining of these algorithms can be used to effectively link large collections of Web data from different domains. To this end, we first present a framework for record linkage over relational data, motivated by the fact that many Web data sources are powered by relational database engines. This framework is based on declarative specification of the linkage requirements by the user and allows linking records in many real-world scenarios. We present algorithms for translation of these requirements to queries that can run over a relational data source, potentially using a semantic knowledge base to enhance the accuracy of link discovery. Effective specification of requirements for linking records across multiple data sources requires understanding the schema of each source, identifying attributes that can be used for linkage, and their corresponding attributes in other sources. Schema or attribute matching is often done with the goal of aligning schemas, so attributes are matched if they play semantically related roles in their schemas. In contrast, we seek to find attributes that can be used to link records between data sources, which we refer to as linkage points. In this thesis, we define the notion of linkage points and present the first linkage point discovery algorithms. We then address the novel problem of how to publish Web data in a way that facilitates record linkage. We hypothesize that careful use of existing, curated Web sources (their data and structure) can guide the creation of conceptual models for semi-structured Web data that in turn facilitate record linkage with these curated sources. Our solution is an end-to-end framework for data transformation and publication, which includes novel algorithms for identification of entity types and their relationships out of semi-structured Web data. A highlight of this thesis is showcasing the application of the proposed algorithms and frameworks in real applications and publishing the results as high-quality data sources on the Web.

Semantic Web and Linked Data community is now the reality of the future of the Web. The standards and technologies defined in this field have opened a strong pathway towards a new era of knowledge management and representation for the computing world. The data structures and the semantic formats introduced by the Semantic Web standards offer a platform for all the data and knowledge providers in the world to present their information in a free, publicly available, semantically tagged, inter-linked, and machine-readable structure. As a result, the adaptation of the Semantic Web standards by data providers creates numerous opportunities for development of new applications which were not possible or, at best, hardly achievable using the current state of Web which is mostly consisted of unstructured or semi-structured data with minimal semantic metadata attached tailored mainly for human-readability. This dissertation tries to introduce a framework for effective analysis of the Semantic Web data towards the development of solutions for a series of related applications. In order to achieve such framework, Wikipedia is chosen as the main knowledge resource largely due to the fact that it is the main and central dataset in Linked Data community. In this work, Wikipedia and its Semantic Web version DBpedia are used to create a semantic graph which constitutes the knowledgebase and the back-end foundation of the framework. The semantic graph introduced in this research consists of two main concepts: entities and topics. The entities act as the knowledge items while topics create the class hierarchy of the knowledge items. Therefore, by assigning entities to various topics, the semantic graph presents all the knowledge items in a categorized hierarchy ready for further processing. Furthermore, this dissertation introduces various analysis algorithms over entity and topic graphs which can be used in a variety of applications, especially in natural language understanding and knowledge management fields. After explaining the details of the analysis algorithms, a number of possible applications are presented and potential solutions to these applications are provided. The main themes of these applications are entity detection, topic identification, and context acquisition. To demonstrate the efficiency of the framework algorithms, some of the applications are developed and comprehensively studied by providing detailed experimental results which are compared with appropriate benchmarks. These results show how the framework can be used in different configurations and how different parameters affect the performance of the algorithms.

Semantic Web and Linked Data community is now the reality of the future of the Web. The standards and technologies defined in this field have opened a strong pathway towards a new era of knowledge management and representation for the computing world. The data structures and the semantic formats introduced by the Semantic Web standards offer a platform for all the data and knowledge providers in the world to present their information in a free, publicly available, semantically tagged, inter-linked, and machine-readable structure. As a result, the adaptation of the Semantic Web standards by data providers creates numerous opportunities for development of new applications which were not possible or, at best, hardly achievable using the current state of Web which is mostly consisted of unstructured or semi-structured data with minimal semantic metadata attached tailored mainly for human-readability. This dissertation tries to introduce a framework for effective analysis of the Semantic Web data towards the development of solutions for a series of related applications. In order to achieve such framework, Wikipedia is chosen as the main knowledge resource largely due to the fact that it is the main and central dataset in Linked Data community. In this work, Wikipedia and its Semantic Web version DBpedia are used to create a semantic graph which constitutes the knowledgebase and the back-end foundation of the framework. The semantic graph introduced in this research consists of two main concepts: entities and topics. The entities act as the knowledge items while topics create the class hierarchy of the knowledge items. Therefore, by assigning entities to various topics, the semantic graph presents all the knowledge items in a categorized hierarchy ready for further processing. Furthermore, this dissertation introduces various analysis algorithms over entity and topic graphs which can be used in a variety of applications, especially in natural language understanding and knowledge management fields. After explaining the details of the analysis algorithms, a number of possible applications are presented and potential solutions to these applications are provided. The main themes of these applications are entity detection, topic identification, and context acquisition. To demonstrate the efficiency of the framework algorithms, some of the applications are developed and comprehensively studied by providing detailed experimental results which are compared with appropriate benchmarks. These results show how the framework can be used in different configurations and how different parameters affect the performance of the algorithms.