No description available.

In order to make a step towards the idea of the Semantic Web it is necessary to research ways how to retrieve semantic information from documents published on the current Web 2.0. As an answer to growing amount of data published in a form of relational tables, the Odalic system, based on the extended TableMiner+ Semantic Table Interpretation algorithm was introduced to provide a convenient way to semantize tabular data using knowledge base disambiguation process. The goal of this thesis is to propose an extended algorithm for the Odalic system, which would allow the system to gather semantic information for tabular data describing products from e-shops, which have very limited presence in the knowl- edge bases. This should be achieved by using a machine learning technique called classification. This thesis consists of several parts - obtaining and preprocessing of the product data from e-shops, evaluation of several classification algorithms in order to select the best-performing one, description of design and implementation of the extended Odalic algorithm, description of its integration into the Odalic system, evaluation of the improved algorithm using the obtained product data and semantization of the product data using the new Odalic algorithm. In the end, the results are concluded and possible...

Le développement rapide des techniques d’extraction d’information a permis de construire de vastes bases de connaissances généralistes. Ces bases de connaissances contiennent des millions de faits portant sur des entités du monde réel, comme des personnes, des lieux, ou des organisations. Ces faits sont accessibles aux ordinateurs, et leur permettent ainsi de “comprendre” le monde réel. Ces bases trouvent donc de nombreuses applications, notamment pour la recherche d’information, le traitement de requêtes, et le raisonnement automatique. Les nombreuses informations contenues dans les bases de connaissances peuvent également être utilisées pour découvrir des motifs intéressants et fréquents dans les données. Cette tâche, l’extraction de règles d’association, permet de comprendre la structure des données ; les règles ainsi obtenues peuvent être employées pour l’analyse de données, la prédiction, et la maintenance de données, entre autres applications. Cette thèse présente deux contributions principales. En premier lieu, nous proposons une nouvelle méthode pour l’extraction de règles d’association dans les bases de connaissances. Cette méthode s’appuie sur un modèle d’extraction qui convient particulièrement aux bases de connaissances potentiellement incomplètes, comme celles qui sont extraites à partir des données du Web. En second lieu, nous montrons que l’extraction de règles peut être utilisée sur les bases de connaissances pour effectuer de nombreuses tâches orientées vers les données. Nous étudions notamment la prédiction de faits, l’alignement de schémas, la mise en forme canonique de bases de connaissances ouvertes, et la prédiction d’annotations de complétude. / The continuous progress of information extraction (IE) techniques has led to the construction of large general-purpose knowledge bases (KBs). These KBs contain millions of computer-readable facts about real-world entities such as people, organizations and places. KBs are important nowadays because they allow computers to “understand” the real world. They are used in multiple applications in Information Retrieval, Query Answering and Automatic Reasoning, among other fields. Furthermore, the plethora of information available in today’s KBs allows for the discovery of frequent patterns in the data, a task known as rule mining. Such patterns or rules convey useful insights about the data. These rules can be used in several applications ranging from data analytics and prediction to data maintenance tasks. The contribution of this thesis is twofold : First, it proposes a method to mine rules on KBs. The method relies on a mining model tailored for potentially incomplete webextracted KBs. Second, the thesis shows the applicability of rule mining in several data-oriented tasks in KBs, namely facts prediction, schema alignment, canonicalization of (open) KBs and prediction of completeness.

No description available.

Dans cette thèse, nous nous intéressons à des problèmes à la croisée de deux domaines, les bases de données et les bases de connaissances. Nous considérons deux problèmes équivalents concernant les requêtes conjonctives avec négation : l'inclusion de requêtes et l'évaluation d'une requête booléenne sous l'hypothèse du monde ouvert. Nous reformulons ces problèmes sous la forme d'un problème de déduction dans un fragment de la logique du premier ordre. Puis nous raffinons des schémas d'algorithmes déjà existants et proposons de nouveaux algorithmes. Pour les étudier et les comparer expérimentalement, nous proposons un générateur aléatoire et analysons l'influence des différents paramètres sur la difficulté des instances du problème étudié. Finalement, à l'aide de cette méthodologie expérimentale, nous comparons les apports des différents raffinements et les algorithmes entre eux. / In this thesis, we consider problems at the intersection of two areas: databases and knowledge bases. We focus on two equivalent problems on conjunctive queries with negation : query containment and query answering with boolean queries while making the open-world assumption. We reformulate these problems as a problem of deduction in a first order logic fragment. Then we refine existing algorithm schemes and propose new algorithms. To study and compare them experimentally, we propose a random generator and we analyze the influence of parameters on problem instances difficulty. Finally, we analyse the contributions of the different refinements and we compare experimentally the algorithms.

La problématique d'interrogation d'une base de données en présence d'une ontologie (OBQA pour "Ontology-based Query Answering") consiste à prendre en compte des connaissances générales, typiquement une ontologie de domaine, lors de l'évaluation d'une requête. Dans le cadre de cette thèse, ces connaissances sont représentées par des formules de la logique du premier ordre appelées "règles existentielles". Les règles existentielles sont aussi connues sous le nom de règles Datalog+/- ou "tuple-generating dependencies". Nous considérons une approche couramment utilisée, qui consiste à réécrire la requête en exploitant les règles de façon à se ramener à un problème classique l'interrogation d'une base de données. Nous définissons un cadre théorique d'étude des algorithmes de réécriture d'une requête conjonctive en une union de requêtes conjonctives, accompagné d'un algorithme de réécriture générique, prenant en paramètre un opérateur de réécriture. Nous proposons ensuite plusieurs opérateurs de réécriture et développons différentes optimisations, que nous évaluons sur des benchmarks du domaine. / The issue of querying a knowledge base, also called Ontology-based Query Answering (OBQA), consists of taking into account general knowledge, typically a domain ontology, when evaluating queries. In this thesis, ontological knowledge is represented by first-order logical formulas, called existential rules. Existential rules are also known as Datalog+/- and tuple-generating dependencies. We adopt a well-known approach, which consists of rewriting the query with the rules to reduce the problem to a classical database query answering problem. We define a theoretical framework to study algorithms that rewrite a conjunctive query into a union of conjunctive queries, as well as a generic rewriting algorithm that takes into account a rewriting operator. Then, we propose several rewriting operators and develop several optimisations, which we evaluate on benchmarks of the domain.

Chinese medicine is one of China's key national assets, an indigenous medical knowledge and practices that serves Chinese for thousands of years. As very little research has been focused on Traditional Chinese Medicine (TCM) from systems of innovation perspective, the topic of study was chosen. This qualitative case study research introduces, defines and explores how TCM organisations collaborate to innovate from an evolutionary, interactive system perspective. In particular, the focus is on the development of knowledge and capabilities related to TCM drug research and production. Thirty one TCM organisation cases were analysed and presented in this study, interpreting their behaviour in terms of ideas drawn mainly from the literatures on systems of innovation, collaboration between organisations and resource (knowledge) based theory of the firm. Actors such as government play various roles in facilitating organisational and sectoral innovation processes. 'Various policy instruments', in particular research funding and institutions (e.g., standards and regulations) were used to enhance innovation and production. Various forms of collaborative networks were found among key actors: enterprises, universities, research organisations and end users. They contribute to the active innovation processes of 'Identification, Selection, Integration and Creation' of tangible and intangible outcomes and changes. Based on the research, new insights were derived as to how indigenous resources (defined as original and/or traditional knowledge and capabilities) may lead to indigenous innovation. This thesis contributes to the academic understanding of systems of innovation operating in the context of indigenous product and related process developments with reference to various actors interplaying in complex networks (systems) of collaborations. New understandings made on the processes of indigenous innovation (using TCM as a case) through investigating the actors' roles, inter-relations and their restless attempts to identify opportunities and problems, select and integrate different indigenous, scientific, technological and managerial knowledge, capabilities, resources and institutions, to create value that may 'fit' in evolutionary terms, the demand of the key actors in the sector.

Answering object queries (i.e. instance retrieval) is a central task in ontology based data access (OBDA). Performing this task involves reasoning with respect to a knowledge base K (i.e. ontology) over some description logic (DL) dialect L. As the expressive power of L grows, so does the complexity of reasoning with respect to K. Therefore, eliminating the need to reason with respect to a knowledge base K is desirable. In this work, we propose an optimization to improve performance of answering object queries by eliminating the need to reason with respect to the knowledge base and, instead, utilizing cached query results when possible. In particular given a DL dialect L, an object query C over some knowledge base K and a set of cached query results S={S1, ..., Sn} obtained from evaluating past queries, we rewrite C into an equivalent query D, that can be evaluated with respect to an empty knowledge base, using cached query results S' = {Si1, ..., Sim}, where S' is a subset of S. The new query D is an interpolant for the original query C with respect to K and S. To find D, we leverage a tool for enumerating interpolants of a given sentence with respect to some theory. We describe a procedure that maps a knowledge base K, expressed in terms of a description logic dialect of first order logic, and object query C into an equivalent theory and query that are input into the interpolant enumerating tool, and resulting interpolants into an object query D that can be evaluated over an empty knowledge base. We show the efficacy of our approach through experimental evaluation on a Lehigh University Benchmark (LUBM) data set, as well as on a synthetic data set, LUBMMOD, that we created by augmenting an LUBM ontology with additional axioms.

It is claimed that economic and social changes are having effects on innovations. Today, innovations have shifted from being only techno-scientific to increasingly also being based on socio-cultural dynamics, with culture, fashion and aesthetic aspects becoming important factors within products. The aim of this study is to research how small food and drink producers in Skåne region innovate and add value to their products. Data was gathered with semi-structured interviews taken with eleven small food production companies and three interviews with people working with regional development. The thesis uses the differential knowledge base model and theories about the experience economy and regional innovation networks, linking the research to regional development. The results indicate that innovations in the food and drink industry are still technologically driven but showing some signs of non-technological elements. This was observable in the companies´ use of stories and symbols as part of the innovations. Most of the producers were adding value to their products by the use of experience staging and storytelling. Participation in networks seemed to enhance the companies’ innovation capabilities. The thesis contributes to studies within economic geography and regional studies by studying innovation, the experience economy and regional innovation networks.

This dissertation provides a capability creation perspective on the story of China’s technological catching up, or resurgence, if viewed from a broader historical perspective. Since the first Asian tigers caught up to modern technological standards (e.g., South Korea, Singapore), two schools of thought have dominated causal explanations (Nelson and Pack, 1999). The first perspective is the conventional accumulation approach, which attributes the major share of growth to the accumulation of physical and human capital, and views learning as a more-or-less automatic byproduct of those investments. The second perspective is the assimilation approach, which emphasizes the arduous learning, risk-taking entrepreneurship, and innovation that is involved in the process and argues that the former proposition neglects this aspect of the endeavour and may therefore lead to erroneous estimates. This dissertation focuses on the second school of thought. Compared to the first-tier Asian tigers, the second-tier tigers, of which China is representative, pose many challenges to the assimilation approach. First, the sheer size of the country results in an unusual scale and scope of activities and interactions in any field. Second, the long history of civilization in China suggests that many modern phenomena have historical roots that are unknown to outsiders and invisible and complex to insiders. The present study aims to contribute a small piece of the puzzle to our understanding of the big picture. By providing an in-depth study of the Chinese information and communication technologies (ICT) sector, this study explores changes that have occurred in the three key building blocks of capability creation; specifically, the sourcing, generation, and appropriation of technological knowledge. A qualitative case study approach was employed for the main, empirical part of the study, which consists of extensive firm-level interviews. Complementary statistical data, including patent data and historical archives, were used to provide context and a deeper look into the study topic. The results are described in five articles. The first article presents establishing overseas research and development (R&D) laboratories as one of the major learning methods for overcoming disadvantages related to dislocation from technology sources and advanced markets. This approach allows China to search for industry-relevant scientific knowledge rather than adopting ready-made technologies introduced by western multinational enterprises in China. The second article describes the modularity-in-design approach, which opens new windows of opportunity for technological advancement. The lack of essential intellectual property rights (IPRs) acts as a key inducement and a factor-saving bias that influences the direction of innovation. When both (international) competitiveness and learning are involved in the catching-up process, the development of industry-wide capability becomes a particularly vital aspect of indigenous innovation. The third article describes the geographic consequences of historically planted industrial capabilities in China’s inland regions, which impact the absorption of different types of industrial knowledge. Fields of industry that are densely populated with patents- IPR thickets- represent a novel situation that was not experienced to the same extent by nations whose technological development occurred earlier. This thesis dedicates two articles to this dimension of knowledge appropriation. The fourth article describes the duality of Chinese ICT patenting, and the fifth article identifies an ambidextrous strategy that depends on where the major competition emerges. In general, the decision to patent and the extent of patenting are determined by four factors: a) the distance to the frontier (Aghion et al., 1997) particularly for technology; b) the nature of the technology (Teece, 1986), but with a rural extension in the case of China; c) the specificities of information (Arrow, 1962) that are embodied in a firm’s origins in China; and d) the supporting institutions that co-evolve in that process. Learning proceeds at different levels: that of individuals, firms, industries, and nations.   This dissertation provides an industry-level perspective on learning and innovation-based technological advancement. / from developing economy to global high-tech competitiveness - the case of Chinese ICT expansion