This licentiate thesis consist of two separate research papers which concern two tangential topics – that of semantic information and that of information security. Both topics are approached by similar methods, i.e. with a concern about conceptual and definitional issues. In Paper I – concerning the concept of information, and a semantic conception thereof – the conceptual, and definitional, issues focus on one property, that of truthfulness. It is argued – against the veridicality thesis – that semantic information need not be truthful. In Paper II – concerning information security – it is argued that the current leading definitions (so-called ‘CIA’ definitions, which define information as secure if, and only if, the properties of confidentiality, integrity, and availability are retained) suffer from both actual and possible counter-examples, and lack an appropriate conceptual sense. On the basis of this criticism a new kind of definitions is proposed and argued for. / <p>QC 20161220</p> / SECURIT

La recherche sémantique de l'information a connu un nouvel essor avec les nouvelles technologies du Web sémantique. Des langages standards permettent aujourd'hui aux logiciels de communiquer par le biais de données écrites dans le vocabulaire d'ontologies de domaine décrivant une sémantique explicite. Cet accès ``sémantique'' à l'information requiert la disponibilité de bases de connaissances décrivant les instances des ontologies de domaine. Cependant, ces bases de connaissances, bien que de plus en plus riches, contiennent relativement peu d'information par comparaison au volume des informations contenu dans les documents du Web.La recherche sémantique de l'information atteint ainsi certaines limites par comparaison à la recherche classique de l'information qui exploite plus largement ces documents. Ces limites se traduisent explicitement par l'absence d'instances de concepts et de relations dans les bases de connaissances construites à partir des documents du Web. Dans cette thèse nous étudions deux directions de recherche différentes afin de permettre de répondre à des requêtes sémantiques dans de tels cas. Notre première étude porte sur la reformulation des requêtes sémantiques des utilisateurs afin d'atteindre des parties de document pertinentes à la place des faits recherchés et manquants dans les bases de connaissances. La deuxième problématique que nous étudions est celle de l'enrichissement des bases de connaissances par des instances de relations.Nous proposons deux solutions pour ces problématiques en exploitant des documents semi-structurés annotés par des concepts ou des instances de concepts. Un des points clés de ces solutions est qu'elles permettent de découvrir des instances de relations sémantiques sans s'appuyer sur des régularités lexico-syntaxiques ou structurelles dans les documents. Nous situons ces deux approches dans la littérature et nous les évaluons avec plusieurs corpus réels extraits du Web. Les résultats obtenus sur des corpus de citations bibliographiques, des corpus d'appels à communication et des corpus géographiques montrent que ces solutions permettent effectivement de retrouver de nouvelles instances relations à partir de documents hétérogènes tout en contrôlant efficacement leur précision. / Semantic information retrieval has known a rapid development with the new Semantic Web technologies. With these technologies, software can exchange and use data that are written according to domain ontologies describing explicit semantics. This ``semantic'' information access requires the availability of knowledge bases describing both domain ontologies and their instances. The most often, these knowledge bases are constructed automatically by annotating document corpora. However, while these knowledge bases are getting bigger, they still contain much less information when comparing them with the HTML documents available on the surface Web.Thus, semantic information retrieval reaches some limits with respect to ``classic'' information retrieval which exploits these documents at a bigger scale. In practice, these limits consist in the lack of concept and relation instances in the knowledge bases constructed from the same Web documents. In this thesis, we study two research directions in order to answer semantic queries in such cases. The first direction consists in reformulating semantic user queries in order to reach relevant document parts instead of the required (and missing) facts. The second direction that we study is the automatic enrichment of knowledge bases with relation instances.We propose two novel solutions for each of these research directions by exploiting semi-structured documents annotated with concept instances. A key point of these solutions is that they don't require lexico-syntactic or structure regularities in the documents. We position these approaches with respect to the state of the art and experiment them on several real corpora extracted from the Web. The results obtained from bibliographic citations, call-for-papers and geographic corpora show that these solutions allow to retrieve new answers/relation instances from heterogeneous documents and rank them efficiently according to their precision.

Im Bereich der städtebasierten siedlungsstrukturellen Analysen spielen Gebäudedaten mit Informationen zur Gebäudenutzung und dem Gebäudetyp eine wichtige Rolle. Auf diesen Daten basiert die Modellierung von demografischen und sozioökonomischen Kenngrößen, welche bei Aufgaben der Siedlungsentwicklung oder in der Infrastrukturplanung zum Einsatz kommen. Vonseiten der amtlichen Vermessungsanstalten stehen kleinräumige und flächendeckende Daten zur Gebäudenutzung nur in begrenztem Umfang zur Verfügung. Eine darauf aufbauende Bevölkerungsabschätzung ist aus diesem Grund nur eingeschränkt möglich. Das Ziel dieser Arbeit war es, die Integration von nutzergenerierten Geodaten aus dem OpenStreetMap (OSM) Projekt für den Einsatz zur Abschätzung gebäudebasierter Bevölkerungs- und Wohnungszahlen zu untersuchen. Der Fokus liegt dabei besonders auf der Abgrenzung von Wohn- und Nichtwohnnutzung innerhalb von Gebäuden. Diese Informationen sind in den amtlichen Geobasisdaten nicht zu finden, können jedoch aus OSM Punkt- und Polygondaten extrahiert werden. Hauptgegenstand der Untersuchung ist die Entwicklung eines Modells zur Integration der Nichtwohnnutzungsinformationen aus OSM, welches Gewerbeinformationen anhand der OSM-Tags analysiert. Dazu war neben einer geeigneten Typologie, die Festlegung von Regeln zur Verarbeitung mehrerer Gewerbe in einem amtlichen Gebäude notwendig. Über räumliche Verschneidungen der Datensätze erfolgt die eigentliche Datenintegration. Zur Umsetzung des Modells wurden drei Python-Skripte erarbeitet, welche alle notwendigen Vorverarbeitungsschritte und anschließenden Modellberechnungen automatisiert durchführen. Zusätzlich zur Bestimmung des Nichtwohnnutzungsanteiles in den Gebäuden, fand eine Wohnung- und Bevölkerungsabschätzung mittels gebäudetypischer Kenngrößen auf Gebäudebasis statt. Mittels der Abschätzungsergebnisse ohne und mit OSM-Gewerbeinformationen, konnte eine Bewertung dieser Methode erfolgen. Eine Beurteilung der Qualität des Modells im Vergleich zur Realität benötigt geeignete Validierungsdaten. Diese wurden in Form von baublockbezogenen statistischen Einwohner- und Wohnungszahlen von der Stadt Dresden bereitgestellt und zur Ergebnisdiskussion herangezogen. Regionale Unterschiede konnten anhand von Übersichts- und Detailkarten sowie statistischen Analysen herausgearbeitet werden. / Building data with information of building uses and building types play an important role for city-based settlement structure analyses. The estimation of demographic and socio-economic parameters is based on this data. They were used in the field of settlement development or in infrastructure planning. The availability of area-wide and small-scale data of building uses from surveying authorities is limited. For this reason, the estimation of population based on this data cannot be realised sufficiently. Therefore, it was the aim of this research paper to analyse the integration of user-generated geodata from OpenStreetMap (OSM)-project for estimating building-based population and housing units. The research focuses on the separation of residential and non-residential usage within buildings. Not being detected in official geodatasets, the information can be retrieved from OSM-point and polygondata. The development of a model for the integration of non-residential information from OSM is the main subject of this research. It contains the analyses of commercial information out of the OSM Tags. Besides an appropriate typology specifications are necessary to process multiple businesses within one official building. The actual data integration occurs with the help of spatial intersections between the datasets. The implementation of the model is based on three Python-scripts, executing all pre-processing and following calculation steps automatically. In addition to the identification of non-residential building-parts, an estimation of population and housing units per building, based on typical building parameters took place. By means of the estimation results with and without OSM-information it was possible to valuate this method. Validation data is necessary to measure the quality of the model in comparison to reality. This datasets was provided by the City of Dresden, consisting of statistical population and building unit numbers based on building blocks, and used for the discussion of the results. To describe regional differences, maps with overview and detailed scales as well as statistical schemata where used.

Les techniques de description des éléments caractéristiques d’une image sont omniprésentes dans de nombreuses applications de vision par ordinateur. Nous proposons à travers ce manuscrit une extension, pour décrire (représenter) et apparier les éléments caractéristiques des images. L’extension proposée consiste en une approche originale pour apprendre, ou estimer, la présence sémantique des éléments caractéristiques locaux dans les images. L’information sémantique obtenue est ensuite exploitée, en conjonction avec le paradigme de sac-de-mots, pour construire un descripteur d’image performant. Le descripteur résultant, est la combinaison de deux types d’informations, locale et contextuelle-sémantique. L’approche proposée peut être généralisée et adaptée à n’importe quel descripteur local d’image, pour améliorer fortement ses performances spécialement quand l’image est soumise à des conditions d’imagerie contraintes. La performance de l’approche proposée est évaluée avec des images réelles aussi bien dans les deux domaines, 2D que 3D. Nous avons abordé dans le domaine 2D, un problème lié à l’appariement des éléments caractéristiques dans des images. Dans le domaine 3D, nous avons résolu les problèmes d’appariement et alignement des vues partielles tridimensionnelles. Les résultats obtenus ont montré qu’avec notre approche, les performances sont nettement meilleures par rapport aux autres méthodes existantes. / This manuscript presents an extension of feature description and matching strategies by proposing an original approach to learn the semantic information of local features. This semantic is then exploited, in conjunction with the bag-of-words paradigm, to build a powerful feature descriptor. The approach, ended up by combining local and context information into a single descriptor, is also a generalized method for improving the performance of the local features, in terms of distinctiveness and robustness under geometric image transformations and imaging conditions. The performance of the proposed approach is evaluated on real world data sets as well as in both the 2D and 3D domains. The 2D domain application addresses the problem of image feature matching while in 3D domain, we resolve the issue of matching and alignment of multiple range images. The evaluation results showed our approach performs significantly better than expected results as well as in comparison with other methods.

Cette thèse doctorale démontre que la difficulté pour un consommateur de se rappeler ses expériences passées de consommation d’un produit préféré influence son désir. Plus particulièrement, ce travail étudie comment le désir est influencé par le type d’information, sémantique ou épisodique, que l’individu se rappelle sur ses expériences passées de consommation pendant une tâche de rappel difficile, ainsi que par la difficulté attendue de la tâche de rappel et par la pression du temps. Nous avons utilisé une méthode expérimentale et avons conduit trois études empiriques. Les hypothèses ont été testées à partir de données collectées de trois échantillons différents : des consommateurs Péruviens, Chinois et Français. Les participants sont principalement des étudiants universitaires. Un total d’onze scénarios expérimentaux ont été présentés aux participants, incluant divers types de produits (boissons rafraîchissantes, produits hédoniques et activités de loisir). Notre contribution peut aider les professionnels en marketing à agir en prenant en compte le rappel des consommations gratifiantes passées. Afin d’évoquer davantage de désir chez le consommateur, les conditions devraient rendre difficile le fait pour celui-ci de se rappeler ses expériences gratifiantes de consommation passées ; les marketeurs devraient se focaliser notamment sur l’information sémantique des expériences passées et soumettre le consommateur à une pression temporelle. Cette recherche se focalise sur un rappel holistique d’expériences passées et sur le processus de récupération d’information à partir de la mémoire, et confirme la théorie du processus dual de Chaiken et Trope (1998) / This thesis demonstrates that difficulty in recalling past consumption of a preferred product influences the desire to consume that product. More specifically, this research evaluate how desire is influenced by what kind of information from past consumption experience is recalled (semantic or episodic information) during a difficult recall task, by the expected difficulty of recall task, and by time pressure. An experimental method was adopted and three empirical studies were conducted. Hypotheses were tested on data collected across different samples: Peruvian, Chinese, and French consumers. Participants were principally university students. A total of eleven experimental scenarios were presented to participants including different types of products (soft drinks, hedonic products, and leisure activities). Questionnaires were administrated by web and face-to-face. Our contribution has the potential to help marketers take action regarding the recall of past rewarding consumptions. To evoke more desire, consumers must be conditioned to difficult recalls of past consumptions of preferred products; marketers must specially focus on semantic information of past experiences and condition consumers with a time pressure. The results suggest that the type of information processed (semantic versus episodic) and time pressure influence the effect of the difficult recall of past consumption on desire. This research focuses on a holistic recall of past experiences and the retrieval process of information from memory, and confirms the Chaiken and Trope (1998)’s Dual-Process Theory

服務創新和發展文化創意產業已成為在這幾年的熱門話題。許多的研究也顯示出文化背景對影響人們做決策和經營管理的重要性；並且，許多相關的文獻也顯示，融合文化來做服務創新的可能性。因此，在這項研究中，我們的目標研究就是要了解是否有任何可以讓我們結合當地的文化資產還有運用資訊科技的協助來促進中小企業達到服務創新的可能性。我們期望可以用文化的角度來看資訊科技於服務創新上的應用，尤其是對中小型企業的業主。 　　在本文中，我們提出了「文化驅動因子」，藉以傳達人受到文化的影響所傳達出來的情感、價值觀和行為等。除此之外，我們更進一步的提出以語意為基礎的資訊系統，希望藉由本系統，我們可以用一種新穎的方式來詮釋當地的文化，並使用當地文化影響下所生成的「文化驅動因子」來激勵中小企業做服務創新。我們相信我們的系統可以激發中小企業，了解他們的文化背景，並進一步實現服務創新的目標。 / To do service innovation and to develop culture and creative industry are becoming a hot issue in these years. A lot of researches have been demonstrating the importance of culture and how it relates or influences to people's decision making and business management. However, few researches to date show the IT enabled use of culture ingredients to do service innovation. Accordingly, in this research we aim to investigate if there is any possibility for us to utilize cultural factors and IT to facilitate the creation service innovation opportunities. Therefore, we intend to view service innovation from the lens of local cultural factors and IT, especially for the small and medium business owners (SMBs). In this paper, we proposed “cultural interpretations” as the emotions, values and behavior, etc. which people convey out through the effect of culture. In addition, we come up with a semantic information system to motive or inspire SMBs with a new way to think about service innovation by leveraging the local culture in terms of the perspective of “cultural interpretations”. We believe our system could motive SMBs to understand their culture context and then achieve the goal of doing service innovation.

In this thesis, a particular class of agent is singled out for examination. In order to provide a guiding metaphor, we speak of control room agents. Our focus is on rational decision- making by such agents, where the circumstances obtaining are such that rationality is bounded. Control room agents, whether human or non-human, need to reason and act in a changing environment with only limited information available to them. Determining the current state of the environment is a central concern for control room agents if they are to reason and act sensibly. A control room agent cannot plan its actions without having an internal representation (epistemic state) of its environment, and cannot make rational decisions unless this representation, to some level of accuracy, reflects the state of its environment. The focus of this thesis is on three aspects regarding the epistemic functioning of a control room agent: 1. How should the epistemic state of a control room agent be represented in order to facilitate logical analysis? 2. How should a control room agent change its epistemic state upon receiving new information? 3. How should a control room agent combine available information from different sources? In describing the class of control room agents as first-order intentional systems hav- ing both informational and motivational attitudes, an agent-oriented view is adopted. The central construct used in the information-theoretic approach, which is qualitative in nature, is the concept of a templated ordering. Representing the epistemic state of a control room agent by a (special form of) tem- plated ordering signals a departure from the many approaches in which only the beliefs of an agent are represented. Templated orderings allow for the representation of both knowledge and belief. A control room agent changes its epistemic state according to a proposed epistemic change algorithm, which allows the agent to select between two well-established forms of belief change operations, namely, belief revision and belief update. The combination of (possibly conflicting) information from different sources has re- ceived a lot of attention in recent years. Using templated orderings for the semantic representation of information, a new family of purely qualitative merging operations is developed. / School of Computing / Ph. D. (Computer Science)

In this thesis, a particular class of agent is singled out for examination. In order to provide a guiding metaphor, we speak of control room agents. Our focus is on rational decision- making by such agents, where the circumstances obtaining are such that rationality is bounded. Control room agents, whether human or non-human, need to reason and act in a changing environment with only limited information available to them. Determining the current state of the environment is a central concern for control room agents if they are to reason and act sensibly. A control room agent cannot plan its actions without having an internal representation (epistemic state) of its environment, and cannot make rational decisions unless this representation, to some level of accuracy, reflects the state of its environment. The focus of this thesis is on three aspects regarding the epistemic functioning of a control room agent: 1. How should the epistemic state of a control room agent be represented in order to facilitate logical analysis? 2. How should a control room agent change its epistemic state upon receiving new information? 3. How should a control room agent combine available information from different sources? In describing the class of control room agents as first-order intentional systems hav- ing both informational and motivational attitudes, an agent-oriented view is adopted. The central construct used in the information-theoretic approach, which is qualitative in nature, is the concept of a templated ordering. Representing the epistemic state of a control room agent by a (special form of) tem- plated ordering signals a departure from the many approaches in which only the beliefs of an agent are represented. Templated orderings allow for the representation of both knowledge and belief. A control room agent changes its epistemic state according to a proposed epistemic change algorithm, which allows the agent to select between two well-established forms of belief change operations, namely, belief revision and belief update. The combination of (possibly conflicting) information from different sources has re- ceived a lot of attention in recent years. Using templated orderings for the semantic representation of information, a new family of purely qualitative merging operations is developed. / School of Computing / Ph. D. (Computer Science)