Institut für Informatik und Computational Science
Refine
Year of publication
- 2018 (42) (remove)
Document Type
- Article (21)
- Other (13)
- Doctoral Thesis (3)
- Part of a Book (2)
- Conference Proceeding (2)
- Postprint (1)
Keywords
- E-Learning (3)
- TPACK (2)
- argument mining (2)
- parsing (2)
- physical computing (2)
- 2-tag system (1)
- ARCS Modell (1)
- ASP (Answer Set Programming) (1)
- Adaptivität (1)
- Answer set programming (1)
- Antwortmengenprogrammierung (1)
- Apps (1)
- Argumentation structure (1)
- Audience Response Systeme (1)
- Autismus (1)
- Automatic Item Generation (1)
- Berliner Modell (1)
- Blended Learning (1)
- Blind users (1)
- Business process intelligence (1)
- CASP (Constraint Answer Set Programming) (1)
- Clock tree (1)
- Computergestützes Training (1)
- Computing with DNA (1)
- Constraint satisfaction (1)
- Course timetabling (1)
- Declare (1)
- Didaktik (1)
- Digital Game Based Learning (1)
- Digitale Medien (1)
- Edge Computing (1)
- Educational timetabling (1)
- Entwurfsprinzipien (1)
- Event mapping (1)
- Game-based learning (1)
- Gesture input (1)
- Hochschul-Apps (1)
- Hochschul-Cloud (1)
- Hochschullehre (1)
- Imperative calculi (1)
- Interaktivität (1)
- Internet of Things (1)
- Key input (1)
- Kompetenzerwerb (1)
- LMS (1)
- Lehrer*innenbildung (1)
- Lern-App (1)
- Lernaufgaben (1)
- Lernmotivation (1)
- M2M (1)
- MQTT (1)
- Minimal perturbation problems (1)
- Mobile Learning (1)
- Mobiles Lernen (1)
- Modeling (1)
- Multi-objective optimization (1)
- Natural language processing (1)
- Onlinelehre (1)
- OpenOLAT (1)
- Planar tactile display (1)
- Polarization (1)
- Process mining (1)
- SAMR (1)
- SMT (SAT Modulo Theories) (1)
- SaaSAbstract (1)
- Schulmaterial (1)
- Screen reader (1)
- Semantic Interoperability (1)
- Sharing (1)
- Single-event transient (SET) (1)
- Splicing (1)
- Splicing processor (1)
- Strategie (1)
- Turing machine (1)
- Type and effect systems (1)
- Unterrichtswerkzeuge (1)
- User Experience (1)
- Virtual reality (1)
- Weiterbildung (1)
- activities (1)
- answer set programming (1)
- argumentation structure (1)
- authentication (1)
- automated driving (1)
- automated guided vehicle routing (1)
- behavioral (1)
- car assembly operations (1)
- classroom material (1)
- computer science education (1)
- constraints (1)
- continuous (1)
- design principles (1)
- didaktische Rekonstruktion (1)
- didaktisches Konzept (1)
- digitale Bildung (1)
- digitale Medien (1)
- e-learning (1)
- educational reconstruction (1)
- eingebettete Systeme (1)
- embedded systems (1)
- gait (1)
- hybrid (1)
- hybrides Problemlösen (1)
- informatische Bildung im Sekundarbereich (1)
- joint lab (1)
- klinisch-praktischer Unterricht (1)
- locomotion (1)
- media (1)
- mobile Applikationen (1)
- mobiles Lernen (1)
- oneM2M Ontology (1)
- open learning (1)
- pdf forms (1)
- physical Computing (1)
- real-walking (1)
- reliability (1)
- resources (1)
- safety (1)
- secondary computer science education (1)
- security (1)
- smartphone (1)
- technische Rahmenbedingungen (1)
- tools (1)
- tools for teaching (1)
- verification (1)
- xAPI (1)
Institute
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.
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.
Nowadays, business processes are increasingly supported by IT services that produce massive amounts of event data during the execution of a process. These event data can be used to analyze the process using process mining techniques to discover the real process, measure conformance to a given process model, or to enhance existing models with performance information. Mapping the produced events to activities of a given process model is essential for conformance checking, annotation and understanding of process mining results. In order to accomplish this mapping with low manual effort, we developed a semi-automatic approach that maps events to activities using insights from behavioral analysis and label analysis. The approach extracts Declare constraints from both the log and the model to build matching constraints to efficiently reduce the number of possible mappings. These mappings are further reduced using techniques from natural language processing, which allow for a matching based on labels and external knowledge sources. The evaluation with synthetic and real-life data demonstrates the effectiveness of the approach and its robustness toward non-conforming execution logs.
teaspoon
(2018)
Answer Set Programming (ASP) is an approach to declarative problem solving, combining a rich yet simple modeling language with high performance solving capacities. We here develop an ASP-based approach to curriculum-based course timetabling (CB-CTT), one of the most widely studied course timetabling problems. The resulting teaspoon system reads a CB-CTT instance of a standard input format and converts it into a set of ASP facts. In turn, these facts are combined with a first-order encoding for CB-CTT solving, which can subsequently be solved by any off-the-shelf ASP systems. We establish the competitiveness of our approach by empirically contrasting it to the best known bounds obtained so far via dedicated implementations. Furthermore, we extend the teaspoon system to multi-objective course timetabling and consider minimal perturbation problems.
In this paper, we consider the computational power of a new variant of networks of splicing processors in which each processor as well as the data navigating throughout the network are now considered to be polarized. While the polarization of every processor is predefined (negative, neutral, positive), the polarization of data is dynamically computed by means of a valuation mapping. Consequently, the protocol of communication is naturally defined by means of this polarization. We show that networks of polarized splicing processors (NPSP) of size 2 are computationally complete, which immediately settles the question of designing computationally complete NPSPs of minimal size. With two more nodes we can simulate every nondeterministic Turing machine without increasing the time complexity. Particularly, we prove that NPSP of size 4 can accept all languages in NP in polynomial time. Furthermore, another computational model that is universal, namely the 2-tag system, can be simulated by NPSP of size 3 preserving the time complexity. All these results can be obtained with NPSPs with valuations in the set as well. We finally show that Turing machines can simulate a variant of NPSPs and discuss the time complexity of this simulation.
We propose a new temporal extension of the logic of Here-and-There (HT) and its equilibria obtained by combining it with dynamic logic over (linear) traces. Unlike previous temporal extensions of HT based on linear temporal logic, the dynamic logic features allow us to reason about the composition of actions. For instance, this can be used to exercise fine grained control when planning in robotics, as exemplified by GOLOG. In this paper, we lay the foundations of our approach, and refer to it as Linear Dynamic Equilibrium Logic, or simply DEL. We start by developing the formal framework of DEL and provide relevant characteristic results. Among them, we elaborate upon the relationships to traditional linear dynamic logic and previous temporal extensions of HT.
Der vorliegende Beitrag berichtet auf der Grundlage von Erfahrungen mit dem Audience Response System (ARS) „Auditorium Mobile Classroom Service“ von Erfolgsfaktoren für den Einsatz in der universitären Lehre. Dabei werden sowohl die technischen Rahmenbedingungen und Herausforderungen der Anwendungen berücksichtigt, als auch die unterschiedlichen didaktischen Konzepte und Ziele der beteiligten Akteure (Studierende, Lehrende und Institution). Ziel ist es, Einflussfaktoren für den erfolgreichen Einsatz sowohl für die Praxis als auch die wissenschaftliche Untersuchung und Weiterentwicklung der Systeme zu benennen und ein heuristisches Framework für Chancen und Herausforderungen beim Einsatz von ARS anzubieten.