Analysing inconsistent information using distance-based measures

There have been a number of proposals for measuring inconsistency in a knowledgebase (i.e. a set of logical formulae). These include measures that consider the minimally inconsistent subsets of the knowledgebase, and measures that consider the paraconsistent models (3 or 4 valued models) of the knowledgebase. In this paper, we present a new approach that considers the amount by which each formula has to be weakened in order for the knowledgebase to be consistent. This approach is based on ideas of knowledge merging by Konienczny and Pino-Perez. We show that this approach gives us measures that are different from existing measures, that have desirable properties, and that can take the significance of inconsistencies into account. The latter is useful when we want to differentiate between inconsistencies that have minor significance from inconsistencies that have major significance. We also show how our measures are potentially useful in applications such as evaluating violations of integrity constraints in databases and for deciding how to act on inconsistency

Ontology Alignment using Biologically-inspired Optimisation Algorithms

It is investigated how biologically-inspired optimisation methods can be used to compute alignments between ontologies. Independent of particular similarity metrics, the developed techniques demonstrate anytime behaviour and high scalability. Due to the inherent parallelisability of these population-based algorithms it is possible to exploit dynamically scalable cloud infrastructures - a step towards the provisioning of Alignment-as-a-Service solutions for future semantic applications

Способи обчислення міри неконсистентностей OWL онтологій

Актуальність теми. Розвиток інформаційно-телекомунікаційних технологій сприяє збільшенню обсягів інформації, необхідної для роботи корпоративних систем. Тому на сьогодні існує проблема ефективної обробки даних. Одним із варіантів рішення цієї задачі є обробка даних в системах з використанням онтологій. Онтологія — формалізоване представлення знань про певну предметну область, придатне для автоматизованої обробки. Таким чином дані охоплюють менший об'єм пам'яті, а інформації з них можна отримати більше. Розмір онтологій невпинно зростає, тому неконсистентність або внутрішнє протиріччя онтології в таких випадках є звичним явищем. Для обробки та аналізу таких онтологій необхідно застосовувати способи обчислення міри неконсистентності, які і будуть розглянуті в даній дисертаційній роботі. Об’єктом дослідження є онтологічні системи, некосистентність при побудові онтологій. Предметом дослідження є способи обчислення міри неконсистентності OWL онтологій. Методи дослідження – методи математичної статистики для аналізу обчислення міри некосистентності OWL онтологій. Мета роботи: підвищення ефективності обробки неконсистентних онтологій шляхом застосування обчислення міри невідновідності; адаптація підходів до обчислення міри неконсистентності онтологій в описовій логіці до OWL онтологій; оптимізація способів обчислення міри неконсистентності онтологій задля зменшення часу їх виконання.Actuality of subject. The development of information and telecommunication technologies contributes to the increase of the amount of information necessary for the work of corporate systems. Therefore, today there is a problem of efficient data processing. One of the solutions to this problem is the processing of data in systems using ontologies. Ontology is a formalized representation of knowledge about a particular subject area, suitable for automated processing. This way, the data covers a smaller amount of memory, and more information can be obtained from it. The size of the ontologies is constantly increasing, so the inconsistency or internal contradiction of ontology in such cases is a common occurrence. For the processing and analysis of such ontologies, it is necessary to use methods for calculating the degree of inconsistency, which will be considered in this thesis. The object of the study is ontological systems, non-consistency in the construction of ontologies. The subject of the study is how to calculate the degree of non-consistency of OWL ontologies. Methods of research - methods of mathematical statistics for the analysis of the calculation of the degree of non-consistency of OWL ontologies. The purpose of the work: to increase the efficiency of processing inconsistent ontologies by applying the calculation of the degree of noncompliance; adaptation of approaches to calculating the degree of inconsistency of ontologies in descriptive logic to OWL ontologies; optimization of methods for calculating the degree of inconsistency of ontologies to reduce the time of their implementation.Актуальность темы. Развитие информационно- телекоммуникационных технологий способствует увеличению объемов информации, необходимой для работы корпоративных систем. Поэтому на сегодняшний день существует проблема эффективной обработки данных. Одним из вариантов решения этой задачи является обработка данных в системах с использованием онтологий. Онтология - формализованное представление знаний об определенной предметной области, пригодное для автоматизированной обработки. Таким образом данные охватывают меньший объем памяти, а информации по ним можно больше. Размер онтологий постоянно растет, поэтому неконсистентнисть или внутреннее противоречие онтологии в таких случаях является обычным явлением. Для обработки и анализа таких онтологий необходимо применять способы вычисления степени неконсистентности, которые и будут рассмотрены в данной диссертационной работе. Объектом исследования является онтологические системы, некосистентнисть при построении онтологий. Предметом исследования являются способы вычисления степени неконсистентности OWL онтологий. Методы исследования - методы математической статистики для анализа вычисления меры некосистентности OWL онтологий. Цель работы: повышение эффективности обработки неконсистентних онтологий путем применения вычисления меры несоответствия; адаптация подходов к вычислению степени неконсистентности онтологий в описательной логике в OWL онтологии; оптимизация способов вычисления меры неконсистентности онтологий для уменьшения времени их выполнения

Efficient Maximum A-Posteriori Inference in Markov Logic and Application in Description Logics

Maximum a-posteriori (MAP) query in statistical relational models computes the most probable world given evidence and further knowledge about the domain. It is arguably one of the most important types of computational problems, since it is also used as a subroutine in weight learning algorithms. In this thesis, we discuss an improved inference algorithm and an application for MAP queries. We focus on Markov logic (ML) as statistical relational formalism. Markov logic combines Markov networks with first-order logic by attaching weights to first-order formulas. For inference, we improve existing work which translates MAP queries to integer linear programs (ILP). The motivation is that existing ILP solvers are very stable and fast and are able to precisely estimate the quality of an intermediate solution. In our work, we focus on improving the translation process such that we result in ILPs having fewer variables and fewer constraints. Our main contribution is the Cutting Plane Aggregation (CPA) approach which leverages symmetries in ML networks and parallelizes MAP inference. Additionally, we integrate the cutting plane inference (Riedel 2008) algorithm which significantly reduces the number of groundings by solving multiple smaller ILPs instead of one large ILP. We present the new Markov logic engine RockIt which outperforms state-of-the-art engines in standard Markov logic benchmarks. Afterwards, we apply the MAP query to description logics. Description logics (DL) are knowledge representation formalisms whose expressivity is higher than propositional logic but lower than first-order logic. The most popular DLs have been standardized in the ontology language OWL and are an elementary component in the Semantic Web. We combine Markov logic, which essentially follows the semantic of a log-linear model, with description logics to log-linear description logics. In log-linear description logic weights can be attached to any description logic axiom. Furthermore, we introduce a new query type which computes the most-probable 'coherent' world. Possible applications of log-linear description logics are mainly located in the area of ontology learning and data integration. With our novel log-linear description logic reasoner ELog, we experimentally show that more expressivity increases quality and that the solutions of optimal solving strategies have higher quality than the solutions of approximate solving strategies

Hypotheses and their dynamics in legal argumentation

We investigate some legal interpretation techniques from the viewpoint of the Argentinian jurisprudence. This allows the proposal of a logical framework –from a computer science perspective– for modeling such specific reasoning techniques towards an appropriate construction of legal arguments. Afterwards, we study the usage of assumptions towards construction of hypotheses. This is proposed in the dynamic context of legal procedures, where the referred argumentation framework evolves as part of the investigation instance prior to the trial. We propose belief revision operators to handle such dynamics, preserving a coherent behavior with regards to the legal interpretation used. Abduction is finally proposed to construct systematic hypothesization, with the objective to bring semi-automatic recommendations to push forward the investigation of a legal case

Supporting Format Migration with Ontology Model Comparison

Die ausschließliche Bewahrung der reinen Bitfolge eines digitalen Dokuments führt nicht dazu, dass zu einem späteren Zeitpunkt auch Information aus dem Dokument extrahiert werden kann. Wenn keine Formatinformation verfügbar ist, muss der Inhalt des Dokuments stattdessen als verloren angesehen werden. Eine Lösung für das Problem ist die (wiederholte) Konvertierung in immer neuere Formate. Entsprechende Verfahren, diese Konvertierungen zu ermöglichen und zu automatisieren sind Teil der aktuellen Forschung. Diese Arbeit geht von der Annahme aus, dass digitale Dokumente als formale Ontologien repräsentiert werden können, was es wiederum ermöglicht, existierende Verfahren aus dem Ontology Matching zu verwenden, um Dokumentenformate aufeinander abzubilden. Bis auf wenige Ausnahmen sind existierende Verfahren beschränkt: Sie bilden Klassen auf Klassen, Rollen auf Rollen und Individuen auf Individuen ab. Solche einfachen Abbildungen sind für komplexe Dokumentenformate unzureichend. In dieser Arbeit wird zum einen eine Methode entwickelt, um einfache Abbildungen heuristisch zu komplexeren Regeln zu verfeinern. Das neue Verfahren basiert auf Tableau-Verfahren für Beschreibungslogiken und verwendet eine modelbasierte Repräsentation von komplexen Korrespondenzen. Ein zweiter Teil verwendet die modelbasierte Darstellung, um Vorschläge für bestmögliche Abbildungen zwischen Dokumenten zu finden. Die hier entwickelte Methode verwendet die semantischen Information sowohl aus dem Tableau- wie auch aus dem Verfeinerungsverfahren. Das Ergebnis ist eine neuartige Methode zur halbautomatischen Ableitung komplexer Abbildungen zwischen beschreibungslogischen Ontologien. Das Verfahren ist zugeschnitten aber nicht beschränkt auf das Feld der Formatmigration.Being able to read successfully the bits and bytes stored inside a digital archive does not necessarily mean we are able to extract meaningful information from an archived digital document. If information about the format of a stored document is not available, the contents of the document are essentially lost. One solution to the problem is format conversion, but due to the amount of documents and formats involved, manual conversion of archived documents is usually impractical. There is thus an open research question to discover suitable technologies to transform existing documents into new document formats and to determine the constraints within which these technologies can be applied successfully. In the present work, it is assumed that stored documents are represented as formal description logic ontologies. This makes it possible to view the translation of document formats as an application of ontology matching, an area for which many methods and algorithms have been developed over the recent years. With very few exceptions, however, current ontology matchers are limited to element-level correspondences matching concepts against concepts, roles against roles, and individuals against individuals. Such simple correspondences are insufficient to describe mappings between complex digital documents. This thesis presents a method to refine simple correspondences into more complex ones in a heuristic fashion utilizing a modified form of description logic tableau reasoning. The refinement process uses a model-based representation of correspondences. Building on the formal semantics, the process also includes methods to avoid the generation of inconsistent or incoherent correspondences. In a second part, this thesis also makes use of the model-based representation to determine the best set of correspondences between two ontologies. The developed similarity measures make use of semantic information from both description logic tableau reasoning as well as from the refinement process. The result is a new method to semi-automatically derive complex correspondences between description logic ontologies tailored but not limited to the context of format migration

From maintaining stability to securing change : Expert perceptions on how the Civilian Security Sector contributes to resilience in Ukraine.

Six years after the Euromaidan, Ukraine has taken significant steps in order to reform its civilian security provision, namely the rule of law and law enforcement, to become more aligned with the standards demanded by the Euromaidan demonstrators. What the civilian security sector (CSS) should look like, and who should participate in the design and the controlling of it, are topical issues in Ukraine today, both local and international interest indicating the relevance of the topic for the society. This research explores whether a popular resilience theory could help to understand why reform is so extensively pursued in the CSS and what meanings are attached to the role of the CSS in the Ukrainian society. The research seeks to answer what could resilience be in the particular security context of Ukraine, and what role should the CSS take in constructing that resilience. Basing on expert interviews and a literature review, this research provides analysis on how particular practices, processes and structures in the CSS are believed to construct resilience in Ukraine: how the rule of law and law enforcement are found to contribute to the recovery of the society from disturbances, how they construct the capacity of the society to adapt to future risks, and how they support coping with shocks today. The research also aims to make a contribution to the theoretical resilience literature by exploring the applicability of the resilience concept to a study of security provision in a local context, namely the Ukrainian security framework. The research finds that the Ukrainian civilian security sector has demonstrated notable capability of building societal resilience, as it has reformed and developed its functions more acceptable to the society, despite the ongoing armed conflict on the Ukrainian territory. Developments such as increasing the inclusion of civil society in the processes of security design and the opening up of the security institutions to public monitoring are found outstanding in the turbulent circumstances in Ukraine today. The reform of the CSS is perceived to represent both recovery and adaptive capability of the society. Furthermore, the CSS reform is believed to have made the society more resilient against risks that await in the future. At the same time, however, the study finds that the prevailing corruption and impunity inside the CSS structures are feared to risk the positive developments and to undermine the role of rule of law and law enforcement institutions as constructors of resilience in the society. With regard to the theoretical resilience framework, the research concludes that resilience thinking seems to well capture meanings attached to the CSS reform in Ukraine: the framework seems helpful in conceptualizing why the CSS is demanded to start to prioritize the protection of citizens (vs. the protection of the state) and the adaptation and recovery of the whole society instead of protecting the ruling elites. However, also difficulties in the application of the framework are identified: some risks, such as those related to the armed conflict, appear to entail elements that are difficult to address using resilience thinking, other security paradigms appearing more useful

Abstract Consequence and Logics - Essays in Honor of Edelcio G. de Souza

Edelcio G. de Souza is a Brazilian logician and philosopher who has researches in the domains of abstract logic, non-classical systems, philosophy of science and the foundations of mathematics. This book is in his honor with the purpose of celebrating his 60th birthday. It contains some articles connected with the above topics and other subjects in logical investigations