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- research-articleJanuary 2019
The Research Core Dataset (KDSF) in the Linked Data context
Procedia Computer Science (PROCS), Volume 146, Issue CPages 29–38https://doi.org/10.1016/j.procs.2019.01.074AbstractThis paper describes our efforts to implement the Research Core Dataset (“Kerndatensatz Forschung”; KDSF) as an ontology in VIVO. KDSF is used in VIVO to record the required metadata on incoming data and to produce reports as an output. While both ...
- research-articleDecember 2018
Collaboration in supply chains for development of CPS enabled by semantic web technologies
The development of Industrial Cyber-Physical Systems (ICPS) requires new ways of collaboration between ICPS vendors and companies which provide them with parts and components. As ICPS extend existing systems, e.g. machines or healthcare equipment, by ...
- research-articleJune 2018
Towards a Knowledge Graph for Science
WIMS '18: Proceedings of the 8th International Conference on Web Intelligence, Mining and SemanticsArticle No.: 1, Pages 1–6https://doi.org/10.1145/3227609.3227689The document-centric workflows in science have reached (or already exceeded) the limits of adequacy. This is emphasized by recent discussions on the increasing proliferation of scientific literature and the reproducibility crisis. This presents an ...
- research-articleFebruary 2016
Polynomial inference of universal automata from membership and equivalence queries
Information and Computation (ICOM), Volume 246, Issue CPages 3–19https://doi.org/10.1016/j.ic.2015.11.005A MAT learning algorithm is presented that infers the universal automaton (UA) for a regular target language, using a polynomial number of queries with respect to that automaton. The UA is one of several canonical characterizations for regular ...
- articleMay 2013
Four one-shot learners for regular tree languages and their polynomial characterizability
Theoretical Computer Science (TCSC), Volume 485Pages 85–106https://doi.org/10.1016/j.tcs.2013.01.003We survey two existing algorithms for the inference of finite-state tree automata from membership queries and a finite positive sample or equivalence queries, and we suggest a reformulation of one of them which we deem necessary to ensure its ...
- articleOctober 2012
Learning in the limit with lattice-structured hypothesis spaces
Theoretical Computer Science (TCSC), Volume 457Pages 111–127https://doi.org/10.1016/j.tcs.2012.07.017We define a collection of language classes which are TxtEx-learnable (learnable in the limit from positive data). The learners map any data input to an element of a fixed lattice, and keep the least upper bound of all lattice elements thus obtained as ...
- ArticleOctober 2011
Distributional learning of simple context-free tree grammars
ALT'11: Proceedings of the 22nd international conference on Algorithmic learning theoryPages 398–412This paper demonstrates how existing distributional learning techniques for context-free grammars can be adapted to simple context-free tree grammars in a straightforward manner once the necessary notions and properties for string languages have been ...
- ArticleJuly 2011
Inference of residual finite-state tree automata from membership queries and finite positive data
DLT'11: Proceedings of the 15th international conference on Developments in language theoryPages 476–477The area of Grammatical Inference centers on learning algorithms: Algorithms that infer a description (e.g., a grammar or an automaton) for an unknown formal language from given information in finitely many steps. Various conceivable learning settings ...
- ArticleMay 2010
String extension learning using lattices
LATA'10: Proceedings of the 4th international conference on Language and Automata Theory and ApplicationsPages 380–391https://doi.org/10.1007/978-3-642-13089-2_32The class of regular languages is not identifiable from positive data in Gold's language learning model. Many attempts have been made to define interesting classes that are learnable in this model, preferably with the associated learner having certain ...
- ArticleJuly 2009
Making Finite-State Methods Applicable to Languages Beyond Context-Freeness via Multi-dimensional Trees
We provide a new term-like representation for multi-dimensional trees as defined by Rogers [1,2] which establishes them as a direct generalization of classical trees. As a consequence these structures can be used as input for finite-state applications ...
- ArticleMarch 2009
Two Equivalent Regularizations for Tree Adjoining Grammars
LATA '09: Proceedings of the 3rd International Conference on Language and Automata Theory and ApplicationsPages 469–480https://doi.org/10.1007/978-3-642-00982-2_40We present and compare two methods of how to make derivation in a Tree Adjoining Grammar a regular process (in the Chomsky hierarchy sense) without loss of expressive power. One regularization method is based on an algebraic operation called Lifting, ...
- ArticleSeptember 2008
A Learning Algorithm for Multi-dimensional Trees, or: Learning Beyond Context-Freeness
ICGI '08: Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and ApplicationsPages 111–124https://doi.org/10.1007/978-3-540-88009-7_9We generalize a learning algorithm by Drewes and Högberg [1] for regular tree languages based on a learning model proposed by Angluin [2] to recognizable tree languages of arbitrarily many dimensions, so-called multi-dimensional trees. Trees over multi-...