L’évolution des finalités de l’université québécoise dans un contexte de mondialisation : analyse critique des politiques publiques de 1998 à 2009

La présente recherche s’intéresse à l’évolution des finalités de l’université québécoise dans le contexte de mondialisation en opérant une analyse de contenu des politiques publiques concernant les universités (1998-2009). Notre démarche, qui s’ancre dans une approche socio-historique, a donné lieu à l’appréhension du concept de mondialisation par ses trois dimensions (économique, politique et culturelle), et celui des finalités de l’université par ses missions (formation, recherche et « troisième mission »). Le cadre conceptuel élaboré par la suite a permis d’examiner l’évolution des finalités de l’université dans sa complexité. L’analyse a permis de constater que les thématiques suivaient rarement une évolution linéaire, subissant tantôt une réification, tantôt une stagnation, ou carrément un changement de sens. L’analyse transversale des deux objets permet de dégager des tensions dialectiques qui s’alignent sur le mouvement des dimensions économique, politique et culturelle de la mondialisation. L’influence de la première entraîne un glissement sémantique qui redéfinit le rôle de l’université ainsi que la nature des savoirs à l’éclairage du discours sur l’économie des savoirs. Au plan de la dimension politique, l’application de la nouvelle gestion publique suscite aussi des glissements sémantiques, telle la réification de la définition de la qualité des missions. La dimension culturelle laisse quant à elle entrevoir une forme d’individualisation des rapports avec l’université, notamment en voyant le contrat social dans lequel l’université doit s’engager avec la société se déplacer vers un contrat de gestion. Si les documents font état d’une dichotomie entre savoirs désintéressés et savoirs utiles, il est proposé dans le cadre de cette recherche de dépasser ces oppositions qui finalement émergent de postures idéologiques.

Analyse de maillages surfaciques par construction et comparaison de modèles moyens et par décomposition par graphes s’appuyant sur les courbures discrètes : application à l’étude de la cornée humaine

Réalisé en cotutelle avec Aix Marseille Université.

Institutional Repositories: New Horizon of Science & Technology Knowledge Transactions

Today higher education system and R&D in science & Technology has undergone tremendous changes from the traditional class room learning system and scholarly communication. Huge volume of Academic output and scientific communications are coming in electronic format. Knowledge management is a key challenge in the current century .Due to the advancement of ICT, Open access movement, Scholarly communications, Institutional repositories, ontology, semantic web, web 2.0 etc has revolutionized knowledge transactions and knowledge management in the field of science & technology. Today higher education has moved into a stage where competitive advantage is gained not just through access of infonnation but more importantly from new Knowledge creations.This paper examines the role of institutional repository in knowledge transactions in current scenario of Higher education.

Author Identification in Malayalam using n-grams

Author identification is the problem of identifying the author of an anonymous text or text whose authorship is in doubt from a given set of authors. The works by different authors are strongly distinguished by quantifiable features of the text. This paper deals with the attempts made on identifying the most likely author of a text in Malayalam from a list of authors. Malayalam is a Dravidian language with agglutinative nature and not much successful tools have been developed to extract syntactic & semantic features of texts in this language. We have done a detailed study on the various stylometric features that can be used to form an authors profile and have found that the frequencies of word collocations can be used to clearly distinguish an author in a highly inflectious language such as Malayalam. In our work we try to extract the word level and character level features present in the text for characterizing the style of an author. Our first step was towards creating a profile for each of the candidate authors whose texts were available with us, first from word n-gram frequencies and then by using variable length character n-gram frequencies. Profiles of the set of authors under consideration thus formed, was then compared with the features extracted from anonymous text, to suggest the most likely author.

Ontology based Framework for News Extraction in Visual Media

Anticipating the increase in video information in future, archiving of news is an important activity in the visual media industry. When the volume of archives increases, it will be difficult for journalists to find the appropriate content using current search tools. This paper provides the details of the study we conducted about the news extraction systems used in different news channels in Kerala. Semantic web technologies can be used effectively since news archiving share many of the characteristics and problems of WWW. Since visual news archives of different media resources follow different metadata standards, interoperability between the resources is also an issue. World Wide Web Consortium has proposed a draft for an ontology framework for media resource which addresses the intercompatiblity issues. In this paper, the w3c proposed framework and its drawbacks is also discussed

Automatic Image Annotation Using SURF Descriptors

In recent years there is an apparent shift in research from content based image retrieval (CBIR) to automatic image annotation in order to bridge the gap between low level features and high level semantics of images. Automatic Image Annotation (AIA) techniques facilitate extraction of high level semantic concepts from images by machine learning techniques. Many AIA techniques use feature analysis as the first step to identify the objects in the image. However, the high dimensional image features make the performance of the system worse. This paper describes and evaluates an automatic image annotation framework which uses SURF descriptors to select right number of features and right features for annotation. The proposed framework uses a hybrid approach in which k-means clustering is used in the training phase and fuzzy K-NN classification in the annotation phase. The performance of the system is evaluated using standard metrics.

Negative Größen bei Diophant?

In this paper we champion Diophantus of Alexandria and Isabella Basmakova against Norbert Schappacher. In two publications ([46] and [47]) he puts forward inter alia two propositions: Questioning Diophantus' originality he considers affirmatively the possibility, that the Arithmetica are the joint work of a team of authors like Bourbaki. And he calls Basmakova's claim (in [5]), that Diophantus uses negative numbers, a "nonsense", reproaching her for her "thoughtlessness". First, we disprove Schappacher's Bourbaki thesis. Second, we investigate the semantic meaning and historical significance of Diophantus' keywords leipsis and mparxis. Next, we discuss Schappacher's epistemology of the history of mathematics and defend Basmakova's methods. Furthermore, we give 33 places where Diophantus uses negative quantities as intermediate results; they appear as differences a - b of positive rational numbers, the subtrahend b being bigger than the minuend a; they each represent the (negative) basis (pleyra) of a square number (tetragonos), which is afterwards computed by the formula (a - b)^2 = a^2 + b^2 - 2ab. Finally, we report how the topic "Diophantus and the negative numbers" has been dealt with by translators and commentators from Maximus Planudes onwards.

Automatische Dienstvermittlung in dienstorientierten Architekturen

Die Technologie dienstorientierter Architekturen (Service-oriented Architectures, kurz SOA) weckt große Visionen auf Seiten der Industrie wie auch der Forschung. Sie hat sich als derzeit ideale Lösung für Umgebungen, in denen sich die Anforderungen an die IT-Bedürfnisse rapide ändern, erwiesen. Heutige IT-Systeme müssen Managementaufgaben wie Softwareinstallation, -anpassung oder -austausch erlauben, ohne dabei den laufenden Betrieb wesentlich zu stören. Die dafür nötige Flexibilität bieten dienstorientierte Architekturen, in denen Softwarekomponenten in Form von Diensten zur Verfügung stehen. Ein Dienst bietet über seine Schnittstelle lokalen wie entfernten Applikationen einen Zugang zu seiner Funktionalität. Wir betrachten im Folgenden nur solche dienstorientierte Architekturen, in denen Dienste zur Laufzeit dynamisch entdeckt, gebunden, komponiert, verhandelt und adaptiert werden können. Eine Applikation kann mit unterschiedlichen Diensten arbeiten, wenn beispielsweise Dienste ausfallen oder ein neuer Dienst die Anforderungen der Applikation besser erfüllt. Eine unserer Grundvoraussetzungen lautet somit, dass sowohl das Dienstangebot als auch die Nachfrageseite variabel sind. Dienstorientierte Architekturen haben besonderes Gewicht in der Implementierung von Geschäftsprozessen. Im Rahmen des Paradigmas Enterprise Integration Architecture werden einzelne Arbeitsschritte als Dienste implementiert und ein Geschäftsprozess als Workflow von Diensten ausgeführt. Eine solche Dienstkomposition wird auch Orchestration genannt. Insbesondere für die so genannte B2B-Integration (Business-to-Business) sind Dienste das probate Mittel, um die Kommunikation über die Unternehmensgrenzen hinaus zu unterstützen. Dienste werden hier in der Regel als Web Services realisiert, welche vermöge BPEL4WS orchestriert werden. Der XML-basierte Nachrichtenverkehr und das http-Protokoll sorgen für eine Verträglichkeit zwischen heterogenen Systemen und eine Transparenz des Nachrichtenverkehrs. Anbieter dieser Dienste versprechen sich einen hohen Nutzen durch ihre öffentlichen Dienste. Zum einen hofft man auf eine vermehrte Einbindung ihrer Dienste in Softwareprozesse. Zum anderen setzt man auf das Entwickeln neuer Software auf Basis ihrer Dienste. In der Zukunft werden hunderte solcher Dienste verfügbar sein und es wird schwer für den Entwickler passende Dienstangebote zu finden. Das Projekt ADDO hat in diesem Umfeld wichtige Ergebnisse erzielt. Im Laufe des Projektes wurde erreicht, dass der Einsatz semantischer Spezifikationen es ermöglicht, Dienste sowohl im Hinblick auf ihre funktionalen als auch ihre nicht-funktionalen Eigenschaften, insbesondere die Dienstgüte, automatisch zu sichten und an Dienstaggregate zu binden [15]. Dazu wurden Ontologie-Schemata [10, 16], Abgleichalgorithmen [16, 9] und Werkzeuge entwickelt und als Framework implementiert [16]. Der in diesem Rahmen entwickelte Abgleichalgorithmus für Dienstgüte beherrscht die automatische Aushandlung von Verträgen für die Dienstnutzung, um etwa kostenpflichtige Dienste zur Dienstnutzung einzubinden. ADDO liefert einen Ansatz, Schablonen für Dienstaggregate in BPEL4WS zu erstellen, die zur Laufzeit automatisch verwaltet werden. Das Vorgehen konnte seine Effektivität beim internationalen Wettbewerb Web Service Challenge 2006 in San Francisco unter Beweis stellen: Der für ADDO entwickelte Algorithmus zur semantischen Dienstkomposition erreichte den ersten Platz. Der Algorithmus erlaubt es, unter einer sehr großenMenge angebotener Dienste eine geeignete Auswahl zu treffen, diese Dienste zu Dienstaggregaten zusammenzufassen und damit die Funktionalität eines vorgegebenen gesuchten Dienstes zu leisten. Weitere Ergebnisse des Projektes ADDO wurden auf internationalen Workshops und Konferenzen veröffentlicht. [12, 11]

Web Service Composition Systems for the Web Service Challenge - A Detailed Review

This report gives a detailed discussion on the system, algorithms, and techniques that we have applied in order to solve the Web Service Challenges (WSC) of the years 2006 and 2007. These international contests are focused on semantic web service composition. In each challenge of the contests, a repository of web services is given. The input and output parameters of the services in the repository are annotated with semantic concepts. A query to a semantic composition engine contains a set of available input concepts and a set of wanted output concepts. In order to employ an offered service for a requested role, the concepts of the input parameters of the offered operations must be more general than requested (contravariance). In contrast, the concepts of the output parameters of the offered service must be more specific than requested (covariance). The engine should respond to a query by providing a valid composition as fast as possible. We discuss three different methods for web service composition: an uninformed search in form of an IDDFS algorithm, a greedy informed search based on heuristic functions, and a multi-objective genetic algorithm.

A Language for Interactive Cooperative Agents

Cooperative behaviour of agents within highly dynamic and nondeterministic domains is an active field of research. In particular establishing highly responsive teamwork, where agents are able to react on dynamic changes in the environment while facing unreliable communication and sensory noise, is an open problem. Moreover, modelling such responsive, cooperative behaviour is difficult. In this work, we specify a novel model for cooperative behaviour geared towards highly dynamic domains. In our approach, agents estimate each other’s decision and correct these estimations once they receive contradictory information. We aim at a comprehensive approach for agent teamwork featuring intuitive modelling capabilities for multi-agent activities, abstractions over activities and agents, and a clear operational semantic for the new model. This work encompasses a complete specification of the new language, ALICA.

Content aggregation on knowledge bases using graph clustering

Recently, research projects such as PADLR and SWAP have developed tools like Edutella or Bibster, which are targeted at establishing peer-to-peer knowledge management (P2PKM) systems. In such a system, it is necessary to obtain provide brief semantic descriptions of peers, so that routing algorithms or matchmaking processes can make decisions about which communities peers should belong to, or to which peers a given query should be forwarded. This paper proposes the use of graph clustering techniques on knowledge bases for that purpose. Using this clustering, we can show that our strategy requires up to 58% fewer queries than the baselines to yield full recall in a bibliographic P2PKM scenario.

User Profile Management and Selection in Context-Aware Service Platforms for Networks Beyond 3G

In recent years, progress in the area of mobile telecommunications has changed our way of life, in the private as well as the business domain. Mobile and wireless networks have ever increasing bit rates, mobile network operators provide more and more services, and at the same time costs for the usage of mobile services and bit rates are decreasing. However, mobile services today still lack functions that seamlessly integrate into users’ everyday life. That is, service attributes such as context-awareness and personalisation are often either proprietary, limited or not available at all. In order to overcome this deficiency, telecommunications companies are heavily engaged in the research and development of service platforms for networks beyond 3G for the provisioning of innovative mobile services. These service platforms are to support such service attributes. Service platforms are to provide basic service-independent functions such as billing, identity management, context management, user profile management, etc. Instead of developing own solutions, developers of end-user services such as innovative messaging services or location-based services can utilise the platform-side functions for their own purposes. In doing so, the platform-side support for such functions takes away complexity, development time and development costs from service developers. Context-awareness and personalisation are two of the most important aspects of service platforms in telecommunications environments. The combination of context-awareness and personalisation features can also be described as situation-dependent personalisation of services. The support for this feature requires several processing steps. The focus of this doctoral thesis is on the processing step, in which the user’s current context is matched against situation-dependent user preferences to find the matching user preferences for the current user’s situation. However, to achieve this, a user profile management system and corresponding functionality is required. These parts are also covered by this thesis. Altogether, this thesis provides the following contributions: The first part of the contribution is mainly architecture-oriented. First and foremost, we provide a user profile management system that addresses the specific requirements of service platforms in telecommunications environments. In particular, the user profile management system has to deal with situation-specific user preferences and with user information for various services. In order to structure the user information, we also propose a user profile structure and the corresponding user profile ontology as part of an ontology infrastructure in a service platform. The second part of the contribution is the selection mechanism for finding matching situation-dependent user preferences for the personalisation of services. This functionality is provided as a sub-module of the user profile management system. Contrary to existing solutions, our selection mechanism is based on ontology reasoning. This mechanism is evaluated in terms of runtime performance and in terms of supported functionality compared to other approaches. The results of the evaluation show the benefits and the drawbacks of ontology modelling and ontology reasoning in practical applications.

Capturing Emergent Semantics from Social Annotation Systems

The ongoing growth of the World Wide Web, catalyzed by the increasing possibility of ubiquitous access via a variety of devices, continues to strengthen its role as our prevalent information and commmunication medium. However, although tools like search engines facilitate retrieval, the task of finally making sense of Web content is still often left to human interpretation. The vision of supporting both humans and machines in such knowledge-based activities led to the development of different systems which allow to structure Web resources by metadata annotations. Interestingly, two major approaches which gained a considerable amount of attention are addressing the problem from nearly opposite directions: On the one hand, the idea of the Semantic Web suggests to formalize the knowledge within a particular domain by means of the "top-down" approach of defining ontologies. On the other hand, Social Annotation Systems as part of the so-called Web 2.0 movement implement a "bottom-up" style of categorization using arbitrary keywords. Experience as well as research in the characteristics of both systems has shown that their strengths and weaknesses seem to be inverse: While Social Annotation suffers from problems like, e. g., ambiguity or lack or precision, ontologies were especially designed to eliminate those. On the contrary, the latter suffer from a knowledge acquisition bottleneck, which is successfully overcome by the large user populations of Social Annotation Systems. Instead of being regarded as competing paradigms, the obvious potential synergies from a combination of both motivated approaches to "bridge the gap" between them. These were fostered by the evidence of emergent semantics, i. e., the self-organized evolution of implicit conceptual structures, within Social Annotation data. While several techniques to exploit the emergent patterns were proposed, a systematic analysis - especially regarding paradigms from the field of ontology learning - is still largely missing. This also includes a deeper understanding of the circumstances which affect the evolution processes. This work aims to address this gap by providing an in-depth study of methods and influencing factors to capture emergent semantics from Social Annotation Systems. We focus hereby on the acquisition of lexical semantics from the underlying networks of keywords, users and resources. Structured along different ontology learning tasks, we use a methodology of semantic grounding to characterize and evaluate the semantic relations captured by different methods. In all cases, our studies are based on datasets from several Social Annotation Systems. Specifically, we first analyze semantic relatedness among keywords, and identify measures which detect different notions of relatedness. These constitute the input of concept learning algorithms, which focus then on the discovery of synonymous and ambiguous keywords. Hereby, we assess the usefulness of various clustering techniques. As a prerequisite to induce hierarchical relationships, our next step is to study measures which quantify the level of generality of a particular keyword. We find that comparatively simple measures can approximate the generality information encoded in reference taxonomies. These insights are used to inform the final task, namely the creation of concept hierarchies. For this purpose, generality-based algorithms exhibit advantages compared to clustering approaches. In order to complement the identification of suitable methods to capture semantic structures, we analyze as a next step several factors which influence their emergence. Empirical evidence is provided that the amount of available data plays a crucial role for determining keyword meanings. From a different perspective, we examine pragmatic aspects by considering different annotation patterns among users. Based on a broad distinction between "categorizers" and "describers", we find that the latter produce more accurate results. This suggests a causal link between pragmatic and semantic aspects of keyword annotation. As a special kind of usage pattern, we then have a look at system abuse and spam. While observing a mixed picture, we suggest that an individual decision should be taken instead of disregarding spammers as a matter of principle. Finally, we discuss a set of applications which operationalize the results of our studies for enhancing both Social Annotation and semantic systems. These comprise on the one hand tools which foster the emergence of semantics, and on the one hand applications which exploit the socially induced relations to improve, e. g., searching, browsing, or user profiling facilities. In summary, the contributions of this work highlight viable methods and crucial aspects for designing enhanced knowledge-based services of a Social Semantic Web.