TY - JOUR A1 - Abdelwahab, Ahmed A1 - Landwehr, Niels T1 - Deep Distributional Sequence Embeddings Based on a Wasserstein Loss JF - Neural processing letters N2 - Deep metric learning employs deep neural networks to embed instances into a metric space such that distances between instances of the same class are small and distances between instances from different classes are large. In most existing deep metric learning techniques, the embedding of an instance is given by a feature vector produced by a deep neural network and Euclidean distance or cosine similarity defines distances between these vectors. This paper studies deep distributional embeddings of sequences, where the embedding of a sequence is given by the distribution of learned deep features across the sequence. The motivation for this is to better capture statistical information about the distribution of patterns within the sequence in the embedding. When embeddings are distributions rather than vectors, measuring distances between embeddings involves comparing their respective distributions. The paper therefore proposes a distance metric based on Wasserstein distances between the distributions and a corresponding loss function for metric learning, which leads to a novel end-to-end trainable embedding model. We empirically observe that distributional embeddings outperform standard vector embeddings and that training with the proposed Wasserstein metric outperforms training with other distance functions. KW - Metric learning KW - Sequence embeddings KW - Deep learning Y1 - 2022 U6 - https://doi.org/10.1007/s11063-022-10784-y SN - 1370-4621 SN - 1573-773X PB - Springer CY - Dordrecht ER - TY - THES A1 - Abdelwahab Hussein Abdelwahab Elsayed, Ahmed T1 - Probabilistic, deep, and metric learning for biometric identification from eye movements N2 - A central insight from psychological studies on human eye movements is that eye movement patterns are highly individually characteristic. They can, therefore, be used as a biometric feature, that is, subjects can be identified based on their eye movements. This thesis introduces new machine learning methods to identify subjects based on their eye movements while viewing arbitrary content. The thesis focuses on probabilistic modeling of the problem, which has yielded the best results in the most recent literature. The thesis studies the problem in three phases by proposing a purely probabilistic, probabilistic deep learning, and probabilistic deep metric learning approach. In the first phase, the thesis studies models that rely on psychological concepts about eye movements. Recent literature illustrates that individual-specific distributions of gaze patterns can be used to accurately identify individuals. In these studies, models were based on a simple parametric family of distributions. Such simple parametric models can be robustly estimated from sparse data, but have limited flexibility to capture the differences between individuals. Therefore, this thesis proposes a semiparametric model of gaze patterns that is flexible yet robust for individual identification. These patterns can be understood as domain knowledge derived from psychological literature. Fixations and saccades are examples of simple gaze patterns. The proposed semiparametric densities are drawn under a Gaussian process prior centered at a simple parametric distribution. Thus, the model will stay close to the parametric class of densities if little data is available, but it can also deviate from this class if enough data is available, increasing the flexibility of the model. The proposed method is evaluated on a large-scale dataset, showing significant improvements over the state-of-the-art. Later, the thesis replaces the model based on gaze patterns derived from psychological concepts with a deep neural network that can learn more informative and complex patterns from raw eye movement data. As previous work has shown that the distribution of these patterns across a sequence is informative, a novel statistical aggregation layer called the quantile layer is introduced. It explicitly fits the distribution of deep patterns learned directly from the raw eye movement data. The proposed deep learning approach is end-to-end learnable, such that the deep model learns to extract informative, short local patterns while the quantile layer learns to approximate the distributions of these patterns. Quantile layers are a generic approach that can converge to standard pooling layers or have a more detailed description of the features being pooled, depending on the problem. The proposed model is evaluated in a large-scale study using the eye movements of subjects viewing arbitrary visual input. The model improves upon the standard pooling layers and other statistical aggregation layers proposed in the literature. It also improves upon the state-of-the-art eye movement biometrics by a wide margin. Finally, for the model to identify any subject — not just the set of subjects it is trained on — a metric learning approach is developed. Metric learning learns a distance function over instances. The metric learning model maps the instances into a metric space, where sequences of the same individual are close, and sequences of different individuals are further apart. This thesis introduces a deep metric learning approach with distributional embeddings. The approach represents sequences as a set of continuous distributions in a metric space; to achieve this, a new loss function based on Wasserstein distances is introduced. The proposed method is evaluated on multiple domains besides eye movement biometrics. This approach outperforms the state of the art in deep metric learning in several domains while also outperforming the state of the art in eye movement biometrics. N2 - Die Art und Weise, wie wir unsere Augen bewegen, ist individuell charakteristisch. Augenbewegungen können daher zur biometrischen Identifikation verwendet werden. Die Dissertation stellt neuartige Methoden des maschinellen Lernens zur Identifzierung von Probanden anhand ihrer Blickbewegungen während des Betrachtens beliebiger visueller Inhalte vor. Die Arbeit konzentriert sich auf die probabilistische Modellierung des Problems, da dies die besten Ergebnisse in der aktuellsten Literatur liefert. Die Arbeit untersucht das Problem in drei Phasen. In der ersten Phase stützt sich die Arbeit bei der Entwicklung eines probabilistischen Modells auf Wissen über Blickbewegungen aus der psychologischen Literatur. Existierende Studien haben gezeigt, dass die individuelle Verteilung von Blickbewegungsmustern verwendet werden kann, um Individuen genau zu identifizieren. Existierende probabilistische Modelle verwenden feste Verteilungsfamilien in Form von parametrischen Modellen, um diese Verteilungen zu approximieren. Die Verwendung solcher einfacher Verteilungsfamilien hat den Vorteil, dass sie robuste Verteilungsschätzungen auch auf kleinen Mengen von Beobachtungen ermöglicht. Ihre Flexibilität, Unterschiede zwischen Personen zu erfassen, ist jedoch begrenzt. Die Arbeit schlägt daher eine semiparametrische Modellierung der Blickmuster vor, die flexibel und dennoch robust individuelle Verteilungen von Blickbewegungsmustern schätzen kann. Die modellierten Blickmuster können als Domänenwissen verstanden werden, das aus der psychologischen Literatur abgeleitet ist. Beispielsweise werden Verteilungen über Fixationsdauern und Sprungweiten (Sakkaden) bei bestimmten Vor- und Rücksprüngen innerhalb des Textes modelliert. Das semiparametrische Modell bleibt nahe des parametrischen Modells, wenn nur wenige Daten verfügbar sind, kann jedoch auch vom parametrischen Modell abweichen, wenn genügend Daten verfügbar sind, wodurch die Flexibilität erhöht wird. Die Methode wird auf einem großen Datenbestand evaluiert und zeigt eine signifikante Verbesserung gegenüber dem Stand der Technik der Forschung zur biometrischen Identifikation aus Blickbewegungen. Später ersetzt die Dissertation die zuvor untersuchten aus der psychologischen Literatur abgeleiteten Blickmuster durch ein auf tiefen neuronalen Netzen basierendes Modell, das aus den Rohdaten der Augenbewegungen informativere komplexe Muster lernen kann. Tiefe neuronale Netze sind eine Technik des maschinellen Lernens, bei der in komplexen, mehrschichtigen Modellen schrittweise abstraktere Merkmale aus Rohdaten extrahiert werden. Da frühere Arbeiten gezeigt haben, dass die Verteilung von Blickbewegungsmustern innerhalb einer Blickbewegungssequenz informativ ist, wird eine neue Aggrgationsschicht für tiefe neuronale Netze eingeführt, die explizit die Verteilung der gelernten Muster schätzt. Die vorgeschlagene Aggregationsschicht für tiefe neuronale Netze ist nicht auf die Modellierung von Blickbewegungen beschränkt, sondern kann als Verallgemeinerung von existierenden einfacheren Aggregationsschichten in beliebigen Anwendungen eingesetzt werden. Das vorgeschlagene Modell wird in einer umfangreichen Studie unter Verwendung von Augenbewegungen von Probanden evaluiert, die Videomaterial unterschiedlichen Inhalts und unterschiedlicher Länge betrachten. Das Modell verbessert die Identifikationsgenauigkeit im Vergleich zu tiefen neuronalen Netzen mit Standardaggregationsschichten und existierenden probabilistischen Modellen zur Identifikation aus Blickbewegungen. Damit das Modell zum Anwendungszeitpunkt beliebige Probanden identifizieren kann, und nicht nur diejenigen Probanden, mit deren Daten es trainiert wurde, wird ein metrischer Lernansatz entwickelt. Beim metrischen Lernen lernt das Modell eine Funktion, mit der die Ähnlichkeit zwischen Blickbewegungssequenzen geschätzt werden kann. Das metrische Lernen bildet die Instanzen in einen neuen Raum ab, in dem Sequenzen desselben Individuums nahe beieinander liegen und Sequenzen verschiedener Individuen weiter voneinander entfernt sind. Die Dissertation stellt einen neuen metrischen Lernansatz auf Basis tiefer neuronaler Netze vor. Der Ansatz repäsentiert eine Sequenz in einem metrischen Raum durch eine Menge von Verteilungen. Das vorgeschlagene Verfahren ist nicht spezifisch für die Blickbewegungsmodellierung, und wird in unterschiedlichen Anwendungsproblemen empirisch evaluiert. Das Verfahren führt zu genaueren Modellen im Vergleich zu existierenden metrischen Lernverfahren und existierenden Modellen zur Identifikation aus Blickbewegungen. KW - probabilistic deep metric learning KW - probabilistic deep learning KW - biometrics KW - eye movements KW - biometrische Identifikation KW - Augenbewegungen KW - probabilistische tiefe neuronale Netze KW - probabilistisches tiefes metrisches Lernen Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-467980 ER - TY - BOOK A1 - Abrahamsson, Pekka A1 - Baddoo, Nathan A1 - Margaria, Tiziana A1 - Messnarz, Richard T1 - Software Process Improvement : 14th europea conference, EuroSpi 2007, Potsdam, Germany, September 26-28, 2007 ; Proceedings T3 - Lecture Notes in Computer Science Y1 - 2007 VL - 4764 PB - Springer CY - Berlin ER - TY - THES A1 - AbuJarour, Mohammed T1 - Enriched service descriptions: sources, approaches and usages Y1 - 2011 CY - Potsdam ER - TY - JOUR A1 - AbuJarour, Mohammed T1 - Information integration in services computing Y1 - 2010 SN - 978-3-86956-036-6 ER - TY - GEN A1 - Afantenos, Stergos A1 - Peldszus, Andreas A1 - Stede, Manfred T1 - Comparing decoding mechanisms for parsing argumentative structures T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Parsing of argumentative structures has become a very active line of research in recent years. Like discourse parsing or any other natural language task that requires prediction of linguistic structures, most approaches choose to learn a local model and then perform global decoding over the local probability distributions, often imposing constraints that are specific to the task at hand. Specifically for argumentation parsing, two decoding approaches have been recently proposed: Minimum Spanning Trees (MST) and Integer Linear Programming (ILP), following similar trends in discourse parsing. In contrast to discourse parsing though, where trees are not always used as underlying annotation schemes, argumentation structures so far have always been represented with trees. Using the 'argumentative microtext corpus' [in: Argumentation and Reasoned Action: Proceedings of the 1st European Conference on Argumentation, Lisbon 2015 / Vol. 2, College Publications, London, 2016, pp. 801-815] as underlying data and replicating three different decoding mechanisms, in this paper we propose a novel ILP decoder and an extension to our earlier MST work, and then thoroughly compare the approaches. The result is that our new decoder outperforms related work in important respects, and that in general, ILP and MST yield very similar performance. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1062 KW - argumentation structure KW - argument mining KW - parsing Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-470527 SN - 1866-8372 IS - 1062 ER - TY - JOUR A1 - Afantenos, Stergos A1 - Peldszus, Andreas A1 - Stede, Manfred T1 - Comparing decoding mechanisms for parsing argumentative structures JF - Argument & Computation N2 - Parsing of argumentative structures has become a very active line of research in recent years. Like discourse parsing or any other natural language task that requires prediction of linguistic structures, most approaches choose to learn a local model and then perform global decoding over the local probability distributions, often imposing constraints that are specific to the task at hand. Specifically for argumentation parsing, two decoding approaches have been recently proposed: Minimum Spanning Trees (MST) and Integer Linear Programming (ILP), following similar trends in discourse parsing. In contrast to discourse parsing though, where trees are not always used as underlying annotation schemes, argumentation structures so far have always been represented with trees. Using the ‘argumentative microtext corpus’ [in: Argumentation and Reasoned Action: Proceedings of the 1st European Conference on Argumentation, Lisbon 2015 / Vol. 2, College Publications, London, 2016, pp. 801–815] as underlying data and replicating three different decoding mechanisms, in this paper we propose a novel ILP decoder and an extension to our earlier MST work, and then thoroughly compare the approaches. The result is that our new decoder outperforms related work in important respects, and that in general, ILP and MST yield very similar performance. KW - Argumentation structure KW - argument mining KW - parsing Y1 - 2018 U6 - https://doi.org/10.3233/AAC-180033 SN - 1946-2166 SN - 1946-2174 VL - 9 IS - 3 SP - 177 EP - 192 PB - IOS Press CY - Amsterdam ER - TY - GEN A1 - Aguado, Felicidad A1 - Cabalar, Pedro A1 - Fandinno, Jorge A1 - Pearce, David A1 - Perez, Gilberto A1 - Vidal, Concepcion T1 - Revisiting explicit negation in answer set programming T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - A common feature in Answer Set Programming is the use of a second negation, stronger than default negation and sometimes called explicit, strong or classical negation. This explicit negation is normally used in front of atoms, rather than allowing its use as a regular operator. In this paper we consider the arbitrary combination of explicit negation with nested expressions, as those defined by Lifschitz, Tang and Turner. We extend the concept of reduct for this new syntax and then prove that it can be captured by an extension of Equilibrium Logic with this second negation. We study some properties of this variant and compare to the already known combination of Equilibrium Logic with Nelson's strong negation. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1104 KW - Answer Set Programming KW - non-monotonic reasoning KW - Equilibrium logic KW - explicit negation Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-469697 SN - 1866-8372 IS - 1104 SP - 908 EP - 924 ER - TY - JOUR A1 - Aguado, Felicidad A1 - Cabalar, Pedro A1 - Fandinno, Jorge A1 - Pearce, David A1 - Perez, Gilberto A1 - Vidal, Concepcion T1 - Forgetting auxiliary atoms in forks JF - Artificial intelligence N2 - In this work we tackle the problem of checking strong equivalence of logic programs that may contain local auxiliary atoms, to be removed from their stable models and to be forbidden in any external context. We call this property projective strong equivalence (PSE). It has been recently proved that not any logic program containing auxiliary atoms can be reformulated, under PSE, as another logic program or formula without them – this is known as strongly persistent forgetting. In this paper, we introduce a conservative extension of Equilibrium Logic and its monotonic basis, the logic of Here-and-There, in which we deal with a new connective ‘|’ we call fork. We provide a semantic characterisation of PSE for forks and use it to show that, in this extension, it is always possible to forget auxiliary atoms under strong persistence. We further define when the obtained fork is representable as a regular formula. KW - Answer set programming KW - Non-monotonic reasoning KW - Equilibrium logic KW - Denotational semantics KW - Forgetting KW - Strong equivalence Y1 - 2019 U6 - https://doi.org/10.1016/j.artint.2019.07.005 SN - 0004-3702 SN - 1872-7921 VL - 275 SP - 575 EP - 601 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Aguado, Felicidad A1 - Cabalar, Pedro A1 - Fandiño, Jorge A1 - Pearce, David A1 - Perez, Gilberto A1 - Vidal-Peracho, Concepcion T1 - Revisiting Explicit Negation in Answer Set Programming JF - Theory and practice of logic programming KW - Answer set programming KW - Non-monotonic reasoning KW - Equilibrium logic KW - Explicit negation Y1 - 2019 U6 - https://doi.org/10.1017/S1471068419000267 SN - 1471-0684 SN - 1475-3081 VL - 19 IS - 5-6 SP - 908 EP - 924 PB - Cambridge Univ. Press CY - New York ER - TY - JOUR A1 - Ahmad, Nadeem A1 - Shoaib, Umar A1 - Prinetto, Paolo T1 - Usability of Online Assistance From Semiliterate Users' Perspective JF - International journal of human computer interaction Y1 - 2015 U6 - https://doi.org/10.1080/10447318.2014.925772 SN - 1044-7318 SN - 1532-7590 VL - 31 IS - 1 SP - 55 EP - 64 PB - Taylor & Francis Group CY - Philadelphia ER - TY - JOUR A1 - Al Laban, Firas A1 - Reger, Martin A1 - Lucke, Ulrike T1 - Closing the Policy Gap in the Academic Bridge JF - Education sciences N2 - The highly structured nature of the educational sector demands effective policy mechanisms close to the needs of the field. That is why evidence-based policy making, endorsed by the European Commission under Erasmus+ Key Action 3, aims to make an alignment between the domains of policy and practice. Against this background, this article addresses two issues: First, that there is a vertical gap in the translation of higher-level policies to local strategies and regulations. Second, that there is a horizontal gap between educational domains regarding the policy awareness of individual players. This was analyzed in quantitative and qualitative studies with domain experts from the fields of virtual mobility and teacher training. From our findings, we argue that the combination of both gaps puts the academic bridge from secondary to tertiary education at risk, including the associated knowledge proficiency levels. We discuss the role of digitalization in the academic bridge by asking the question: which value does the involved stakeholders expect from educational policies? As a theoretical basis, we rely on the model of value co-creation for and by stakeholders. We describe the used instruments along with the obtained results and proposed benefits. Moreover, we reflect on the methodology applied, and we finally derive recommendations for future academic bridge policies. KW - policy evaluation KW - higher education KW - virtual mobility KW - teacher training Y1 - 2022 U6 - https://doi.org/10.3390/educsci12120930 SN - 2227-7102 VL - 12 IS - 12 PB - MDPI CY - Basel ER - TY - GEN A1 - Al Laban, Firas A1 - Reger, Martin A1 - Lucke, Ulrike T1 - Closing the Policy Gap in the Academic Bridge T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - The highly structured nature of the educational sector demands effective policy mechanisms close to the needs of the field. That is why evidence-based policy making, endorsed by the European Commission under Erasmus+ Key Action 3, aims to make an alignment between the domains of policy and practice. Against this background, this article addresses two issues: First, that there is a vertical gap in the translation of higher-level policies to local strategies and regulations. Second, that there is a horizontal gap between educational domains regarding the policy awareness of individual players. This was analyzed in quantitative and qualitative studies with domain experts from the fields of virtual mobility and teacher training. From our findings, we argue that the combination of both gaps puts the academic bridge from secondary to tertiary education at risk, including the associated knowledge proficiency levels. We discuss the role of digitalization in the academic bridge by asking the question: which value does the involved stakeholders expect from educational policies? As a theoretical basis, we rely on the model of value co-creation for and by stakeholders. We describe the used instruments along with the obtained results and proposed benefits. Moreover, we reflect on the methodology applied, and we finally derive recommendations for future academic bridge policies. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1310 KW - policy evaluation KW - higher education KW - virtual mobility KW - teacher training Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-583572 SN - 1866-8372 IS - 1310 ER - TY - THES A1 - Al-Areqi, Samih Taha Mohammed T1 - Semantics-based automatic geospatial service composition T1 - Semantikbasierte automatische Komposition von GIS-Diensten N2 - Although it has become common practice to build applications based on the reuse of existing components or services, technical complexity and semantic challenges constitute barriers to ensuring a successful and wide reuse of components and services. In the geospatial application domain, the barriers are self-evident due to heterogeneous geographic data, a lack of interoperability and complex analysis processes. Constructing workflows manually and discovering proper services and data that match user intents and preferences is difficult and time-consuming especially for users who are not trained in software development. Furthermore, considering the multi-objective nature of environmental modeling for the assessment of climate change impacts and the various types of geospatial data (e.g., formats, scales, and georeferencing systems) increases the complexity challenges. Automatic service composition approaches that provide semantics-based assistance in the process of workflow design have proven to be a solution to overcome these challenges and have become a frequent demand especially by end users who are not IT experts. In this light, the major contributions of this thesis are: (i) Simplification of service reuse and workflow design of applications for climate impact analysis by following the eXtreme Model-Driven Development (XMDD) paradigm. (ii) Design of a semantic domain model for climate impact analysis applications that comprises specifically designed services, ontologies that provide domain-specific vocabulary for referring to types and services, and the input/output annotation of the services using the terms defined in the ontologies. (iii) Application of a constraint-driven method for the automatic composition of workflows for analyzing the impacts of sea-level rise. The application scenario demonstrates the impact of domain modeling decisions on the results and the performance of the synthesis algorithm. N2 - Obwohl es gängige Praxis geworden ist, Anwendungen basierend auf der Wiederverwendung von existierenden Komponenten oder Diensten zu bauen, stellen technische Komplexität und semantische Herausforderungen Hindernisse beim Sicherstellen einer erfolgreichen und breiten Wiederverwendungen von Komponenten und Diensten. In der geowissenschaftlichen Anwendungsdomäne sind die Hindernisse durch heterogene geografische Daten, fehlende Interoperabilität und komplexe Analyseprozessen besonders offensichtlich. Workflows manuell zu konstruieren und passende Dienste und Daten zu finden, welche die Nutzerabsichten und -präferenzen abdecken, ist schwierig und zeitaufwändig besonders für Nutzer, die nicht in der Softwareentwicklung ausgebildet sind. Zudem erhöhen die verschiedenen Zielrichtungen der Umweltmodellierung für die Bewertung der Auswirkungen von Klimaänderungen und die unterschiedlichen Typen geografischer Daten (z.B. Formate, Skalierungen, und Georeferenzsysteme) die Komplexität. Automatische Dienstkompositionsansätze, die Semantik-basierte Unterstützung im Prozess des Workflowdesigns zur Verfügung stellen, haben bewiesen eine Lösung zur Bewältigung dieser Herausforderungen zu sein und sind besonders von Endnutzern, die keine IT-Experten sind, eine häufige Forderung geworden. Unter diesem Gesichtspunkt sind die Hauptbeiträge dieser Doktorarbeit: I. Vereinfachung der Wiederverwendung von Diensten und des Workflowdesigns von Klimafolgenanalysen durch Anwendung des Paradigma des eXtreme Model-Driven Development (XMDD) II. Design eines semantischen Domänenmodells für Anwendungen der Klimafolgenanalysen, welches speziell entwickelte Dienste, Ontologien (die domänen-spezifisches Vokabular zur Verfügung stellen, um Typen und Dienste zu beschreiben), und Eingabe-/Ausgabe-Annotationen der Dienste (unter Verwendung von Begriffen, die in den Ontologien definiert sind) enthält. III. Anwendungen einer Constraint-getriebenen Methode für die automatische Komposition von Workflows zum Analysieren der Auswirkungen des Meeresspiegelanstiegs. Das Anwendungsszenario demonstriert die Auswirkung von Domänenmodellierungsentscheidungen auf die Ergebnisse und die Laufzeit des Synthesealgorithmus. KW - geospatial services KW - service composition KW - scientific workflows KW - semantic domain modeling KW - ontologies KW - climate impact analysis KW - GIS-Dienstkomposition KW - Wissenschaftlichesworkflows KW - semantische Domänenmodellierung KW - Ontologien KW - Klimafolgenanalyse Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-402616 ER - TY - THES A1 - Al-Saffar, Loay Talib Ahmed T1 - Analysing prerequisites, expectations, apprehensions, and attitudes of University students studying computer science Y1 - 2016 ER - TY - BOOK A1 - Al-Saffar, Loay Talib Ahmed T1 - Where girls the role of boys in CS - attitudes of CS students in a female-dominated environment Y1 - 2013 SN - 978-3-86956-220-9 ER - TY - THES A1 - Al-Saffar, Loay Talib Ahmed T1 - Analysing prerequisites, expectations, apprehensions, and attitudes of university students studying Computer science T1 - Analyse von Voraussetzungen, Erwartungen, Haltungen, Einstellungen und Befürchtungen von Bachelor-Studierenden der Informatik N2 - The main objective of this dissertation is to analyse prerequisites, expectations, apprehensions, and attitudes of students studying computer science, who are willing to gain a bachelor degree. The research will also investigate in the students’ learning style according to the Felder-Silverman model. These investigations fall in the attempt to make an impact on reducing the “dropout”/shrinkage rate among students, and to suggest a better learning environment. The first investigation starts with a survey that has been made at the computer science department at the University of Baghdad to investigate the attitudes of computer science students in an environment dominated by women, showing the differences in attitudes between male and female students in different study years. Students are accepted to university studies via a centrally controlled admission procedure depending mainly on their final score at school. This leads to a high percentage of students studying subjects they do not want. Our analysis shows that 75% of the female students do not regret studying computer science although it was not their first choice. And according to statistics over previous years, women manage to succeed in their study and often graduate on top of their class. We finish with a comparison of attitudes between the freshman students of two different cultures and two different university enrolment procedures (University of Baghdad, in Iraq, and the University of Potsdam, in Germany) both with opposite gender majority. The second step of investigation took place at the department of computer science at the University of Potsdam in Germany and analyzes the learning styles of students studying the three major fields of study offered by the department (computer science, business informatics, and computer science teaching). Investigating the differences in learning styles between the students of those study fields who usually take some joint courses is important to be aware of which changes are necessary to be adopted in the teaching methods to address those different students. It was a two stage study using two questionnaires; the main one is based on the Index of Learning Styles Questionnaire of B. A. Solomon and R. M. Felder, and the second questionnaire was an investigation on the students’ attitudes towards the findings of their personal first questionnaire. Our analysis shows differences in the preferences of learning style between male and female students of the different study fields, as well as differences between students with the different specialties (computer science, business informatics, and computer science teaching). The third investigation looks closely into the difficulties, issues, apprehensions and expectations of freshman students studying computer science. The study took place at the computer science department at the University of Potsdam with a volunteer sample of students. The goal is to determine and discuss the difficulties and issues that they are facing in their study that may lead them to think in dropping-out, changing the study field, or changing the university. The research continued with the same sample of students (with business informatics students being the majority) through more than three semesters. Difficulties and issues during the study were documented, as well as students’ attitudes, apprehensions, and expectations. Some of the professors and lecturers opinions and solutions to some students’ problems were also documented. Many participants had apprehensions and difficulties, especially towards informatics subjects. Some business informatics participants began to think of changing the university, in particular when they reached their third semester, others thought about changing their field of study. Till the end of this research, most of the participants continued in their studies (the study they have started with or the new study they have changed to) without leaving the higher education system. N2 - Thema der Dissertation ist die Untersuchung von Voraussetzungen, Erwartungen, Haltungen, Einstellungen und Befürchtungen von Bachelor Studierenden der Informatik. Darüber hinaus werden in der vorliegenden Analyse anhand des Solomon/Felder-Modells Lerntypen unter den Informatik-Studierenden untersucht mit dem Ziel, mittels einer vorteilhafter gestalteten Lernumgebung zur Lernwirksamkeit und zur Reduktion der Abbrecherquote beizutragen. Zunächst werden anhand einer Vergleichsstudie zwischen Informatik-Studierenden an der Universität Bagdad und an der Universität Potsdam sowie jeweils zwischen männlichen und weiblichen Studierenden Unterschiede in der Wahrnehmung des Fachs herausgearbeitet. Hierzu trägt insbesondere das irakische Studienplatzvergabeverfahren bei, das den Studierenden nur wenig Freiheiten lässt, ein Studienfach zu wählen mit dem Ergebnis, dass viele Studierende, darunter überwiegend weibliche Studierende, gegen ihre Absicht Informatik studieren. Dennoch arrangieren sich auch die weiblichen Studierenden mit dem Fach und beenden das Studium oft mit Best-Noten. Der zweite Teil der Dissertation analysiert Lernstile von Studierenden des Instituts für Informatik der Universität Potsdam auf der Grundlage des Modells von Solomon/Felder mit dem Ziel, Hinweise für eine verbesserte Gestaltung der Lehrveranstaltungen zu gewinnen, die Lernende in der für sie geeigneten Form anspricht. Die Ergebnisse zeigen die Schwierigkeit, dieses Ziel zu erreichen, denn sowohl männliche und weibliche Studierende als auch Studierende von Informatik, Wirtschaftsinformatik und Lehramt Informatik weisen deutliche Unterschiede in den präferierten Lernstilen auf. In einer dritten qualitativen Studie wurden mit Studierenden von Informatik, Wirtschaftsinformatik und Lehramt Informatik Interviews über einen Zeitraum der ersten drei Studiensemester geführt, um einen detaillierten Einblick in Haltungen, Einstellungen und Erwartungen zum Studium zu gewinnen sowie Probleme zu ermitteln, die möglicherweise zum Abbruch des Studiums oder zum Wechsel des Fachs oder der Universität führen können. KW - computer science education KW - dropout KW - changing the university KW - changing the study field KW - Computer Science KW - business informatics KW - study problems KW - tutorial section KW - higher education KW - teachers KW - professors KW - Informatikvoraussetzungen KW - Studentenerwartungen KW - Studentenhaltungen KW - Universitätseinstellungen KW - Bachelorstudierende der Informatik KW - Abbrecherquote KW - Wirtschaftsinformatik KW - Informatik KW - Universität Potsdam KW - Universität Bagdad KW - Probleme in der Studie KW - Lehrer KW - Professoren KW - Theoretischen Vorlesungen KW - Programmierung KW - Anleitung KW - Hochschulsystem KW - Informatik-Studiengänge KW - Didaktik der Informatik Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-98437 ER - TY - THES A1 - Albrecht, Alexander T1 - Understanding and managing extract-transform-load systems Y1 - 2013 ER - TY - GEN A1 - Alhosseini Almodarresi Yasin, Seyed Ali A1 - Bin Tareaf, Raad A1 - Najafi, Pejman A1 - Meinel, Christoph T1 - Detect me if you can BT - Spam Bot Detection Using Inductive Representation Learning T2 - Companion Proceedings of The 2019 World Wide Web Conference N2 - Spam Bots have become a threat to online social networks with their malicious behavior, posting misinformation messages and influencing online platforms to fulfill their motives. As spam bots have become more advanced over time, creating algorithms to identify bots remains an open challenge. Learning low-dimensional embeddings for nodes in graph structured data has proven to be useful in various domains. In this paper, we propose a model based on graph convolutional neural networks (GCNN) for spam bot detection. Our hypothesis is that to better detect spam bots, in addition to defining a features set, the social graph must also be taken into consideration. GCNNs are able to leverage both the features of a node and aggregate the features of a node’s neighborhood. We compare our approach, with two methods that work solely on a features set and on the structure of the graph. To our knowledge, this work is the first attempt of using graph convolutional neural networks in spam bot detection. KW - Social Media Analysis KW - Bot Detection KW - Graph Embedding KW - Graph Convolutional Neural Networks Y1 - 2019 SN - 978-1-4503-6675-5 U6 - https://doi.org/10.1145/3308560.3316504 SP - 148 EP - 153 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Alnemr, Rehab T1 - Context-aware Reputation in SOA and future internet Y1 - 2010 SN - 978-3-86956-036-6 ER -