Trend detection in folksonomies

As the number of resources on the web exceeds by far the number of documents one can track, it becomes increasingly difficult to remain up to date on ones own areas of interest. The problem becomes more severe with the increasing fraction of multimedia data, from which it is difficult to extract some conceptual description of their contents. One way to overcome this problem are social bookmark tools, which are rapidly emerging on the web. In such systems, users are setting up lightweight conceptual structures called folksonomies, and overcome thus the knowledge acquisition bottleneck. As more and more people participate in the effort, the use of a common vocabulary becomes more and more stable. We present an approach for discovering topic-specific trends within folksonomies. It is based on a differential adaptation of the PageRank algorithm to the triadic hypergraph structure of a folksonomy. The approach allows for any kind of data, as it does not rely on the internal structure of the documents. In particular, this allows to consider different data types in the same analysis step. We run experiments on a large-scale real-world snapshot of a social bookmarking system.

Spezifität der quantitativen Resistenz von Blättern und Früchten der Tomate (Lycopersicon ssp. L.) gegenüber Phytophthora infestans (Mont.) de Bary.

Ziel der vorliegenden Arbeit war es, einen Beitrag zur Resistenzforschung bei Tomaten gegenüber P. infestans zu leisten, um erste Grundlagen für eine mögliche Züchtungsstrategie auf Basis unterschiedlicher quantitativer Resistenzen zu erarbeiten. Hierzu wurde untersucht, inwieweit unterschiedliche qualitative und quantitative Resistenzen bei Tomatenblättern und -früchten vorliegen, und ob hierfür verantwortliche Mechanismen identifiziert werden können. Zudem wurde untersucht, ob isolatspezifische quantitative Resistenzen identifiziert werden können. Zu diesem Zweck wurde mit einer erweiterten Clusteranalyse, basierend auf einer modifizierten Sanghvi-T2 Distanz, ein statistisches Verfahren entwickelt, welches die Identifikation von quantitativen, isolatspezifischen Resistenzen unter der Berücksichtigung der Variabilität ermöglicht. Des weiteren wurde geprüft, inwieweit zwischen den Resistenzausprägungen auf dem Blatt und den Resistenzausprägungen auf der Frucht ein Zusammenhang besteht und inwieweit die im Labor beobachteten Resistenzen unter Freilandbedingungen eine Rolle spielen. Im Labortest wurde die qualitative und quantitative Blattresistenz von 109 Akzessionen aus elf Lycopersicon und Solanum Arten gegenüber zwölf unterschiedlich aggressiven und teilweise auch unterschiedlich virulenten P. infestans Isolaten untersucht (Kap. 3). Die Früchte von 38 Tomatensorten wurden auf ihre Resistenz gegenüber drei P. infestans Isolaten geprüft. Zusätzlich wurde der Einfluss der Fruchtnachreife auf die Resistenzeigenschaften der Tomatenfrüchte gegenüber P. infestans analysiert (Kap. 4). Insgesamt 40 Sorten wurden auch unter Feldbedingungen auf Blatt- und Fruchtbefall untersucht (Kap. 5). Die frühen Stadien der Infektion von Tomatenblättern mit P. infestans Sporangien wurden mikroskopisch bei acht Tomatensorten mit unterschiedlichen quantitativen Reaktionsprofilen und drei Isolaten untersucht (Kap. 6). Hierzu wurden die Entwicklungsstadien von P. infestans Sporangien nach 24h, 48h und 60h nach der Inokulation auf und im Blatt mit der Calcofluor und der KOH - Anilin Blau Färbung sichtbar gemacht. Das Auftreten und die Lokalisation von H2O2 im Blatt nach 48h und 60h nach der Inokulation in Reaktion auf die Infektion wurde mithilfe einer DAB (3,3′ - Diaminobenzidine) Färbung untersucht. Es wurden einige, z.T. auch wahrscheinlich neue, qualitative Blattresistenzen gegenüber P. infestans gefunden, jedoch war keine der 109 Akzessionen vollständig resistent gegenüber allen Isolaten. Für die quantitative Resistenz von Blättern lagen in vielen Fällen isolatspezifische Unterschiede vor. Die Sorte x Isolat Interaktionen konnten mit Hilfe der erweiterten Clusteranalyse erfolgreich analysiert werden und die Akzessionen in Gruppen mit unterschiedlichen quantitativen Resistenzprofilen bzgl. der Interaktion mit den Isolaten und des Resistenzniveaus eingeteilt werden. Für die Fruchtresistenz konnten keine qualitativen Resistenzen gegenüber den drei getesteten Isolaten gefunden werden. Im Gegensatz dazu unterschieden sich die Tomatensorten in ihrer quantitativen Resistenz und Sorten und Isolate interagierten signifikant. Auch für die Fruchtresistenz konnten Gruppen mit unterschiedlichen quantitativen Reaktionsprofilen gebildet werden. Insgesamt nimmt die Anfälligkeit von Tomatenfrüchten mit zunehmender Reife kontinuierlich und signifikant ab. Unter Laborbedingungen korrelierten nur die Sporulationskapazität der Früchte und der prozentuale Blattbefall. Im Feldversuch über zwei Jahre und mit bis zu 40 Tomatensorten war der Zusammenhang hoch signifikant, jedoch asymptotisch, d.h. bereits bei sehr geringem Blattbefall war der Fruchtbefall sehr hoch. Bei den Tomatenherkünften, die sowohl im Labor als auch im Feld auf ihre Anfälligkeit getestet wurden, erschienen die Blattanfälligkeiten ähnlich, während kein klarer Zusammenhang zwischen der Fruchtanfälligkeit im Feld und im Labor bestand. Die Entwicklung von P. infestans auf der Blattoberfläche war unabhängig von der Sorte. Sowohl beim Eindringen und der Etablierung von P. infestans ins Blatt als auch bei der damit verbunden H2O2 Aktivität im Wirt wurden deutliche isolat- und sortenspezifische Effekte gefunden, die aber nur zum Teil mit den quantitativen Unterschieden der Blattresistenz korrespondierten. Sorten, die bei hoher Resistenz unterschiedliche Reaktionsprofile aufweisen, sind grundsätzlich interessante Kreuzungspartner, um die quantitative Resistenz gegenüber P. infestans zu verbessern. Hier sind vor allem Sorten, die sich auch in ihrer H2O2 Aktivität unterscheiden von Interesse.

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.

Identification of Problem-based learning components and their effects on graduates' competencies

This study investigated the relationship between higher education and the requirement of the world of work with an emphasis on the effect of problem-based learning (PBL) on graduates' competencies. The implementation of full PBL method is costly (Albanese & Mitchell, 1993; Berkson, 1993; Finucane, Shannon, & McGrath, 2009). However, the implementation of PBL in a less than curriculum-wide mode is more achievable in a broader context (Albanese, 2000). This means higher education institutions implement only a few PBL components in the curriculum. Or a teacher implements a few PBL components at the courses level. For this kind of implementation there is a need to identify PBL components and their effects on particular educational outputs (Hmelo-Silver, 2004; Newman, 2003). So far, however there has been little research about this topic. The main aims of this study were: (1) to identify each of PBL components which were manifested in the development of a valid and reliable PBL implementation questionnaire and (2) to determine the effect of each identified PBL component to specific graduates' competencies. The analysis was based on quantitative data collected in the survey of medicine graduates of Gadjah Mada University, Indonesia. A total of 225 graduates responded to the survey. The result of confirmatory factor analysis (CFA) showed that all individual constructs of PBL and graduates' competencies had acceptable GOFs (Goodness-of-fit). Additionally, the values of the factor loadings (standardize loading estimates), the AVEs (average variance extracted), CRs (construct reliability), and ASVs (average shared squared variance) showed the proof of convergent and discriminant validity. All values indicated valid and reliable measurements. The investigation of the effects of PBL showed that each PBL component had specific effects on graduates' competencies. Interpersonal competencies were affected by Student-centred learning (β = .137; p < .05) and Small group components (β = .078; p < .05). Problem as stimulus affected Leadership (β = .182; p < .01). Real-world problems affected Personal and organisational competencies (β = .140; p < .01) and Interpersonal competencies (β = .114; p < .05). Teacher as facilitator affected Leadership (β = 142; p < .05). Self-directed learning affected Field-related competencies (β = .080; p < .05). These results can help higher education institution and educator to have informed choice about the implementation of PBL components. With this information higher education institutions and educators could fulfil their educational goals and in the same time meet their limited resources. This study seeks to improve prior studies' research method in four major ways: (1) by indentifying PBL components based on theory and empirical data; (2) by using latent variables in the structural equation modelling instead of using a variable as a proxy of a construct; (3) by using CFA to validate the latent structure of the measurement, thus providing better evidence of validity; and (4) by using graduate survey data which is suitable for analysing PBL effects in the frame work of the relationship between higher education and the world of work.