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Preprint
Intelligent structuring and reducing of association rules with formal concept analysis
(2001)
Association rules are used to investigate large databases. The analyst is usually confronted with large lists of such rules and has to find the most relevant ones for his purpose. Based on results about knowledge representation within the theoretical framework of Formal Concept Analysis, we present relatively small bases for association rules from which all rules can be deduced. We also provide algorithms for their calculation.
Preprint
Degrees of Free Word-Order and Freely Rewriting Restarting Automata
(Universität Kassel, FB 17, Mathematik/Informatik, 2005)
In natural languages with a high degree of word-order freedom syntactic phenomena like dependencies (subordinations) or valencies do not depend on the word-order (or on the individual positions of the individual words). This means that some permutations of sentences of these languages are in some (important) sense syntactically equivalent. Here we study this phenomenon in a formal way. Various types of j-monotonicity for restarting automata can serve as parameters for the degree of word-order freedom and for the ...
Preprint
On the Descriptional Complexity of Simple RL-Automata
(2006)
Analysis by reduction is a method used in linguistics for checking the correctness of sentences of natural languages.
This method is modelled by restarting automata. Here we study a new type of restarting automaton, the so-called t-sRL-automaton, which is an RL-automaton that is rather restricted in that it has a window of size 1 only, and that it works under a minimal acceptance condition.
On the other hand, it is allowed to perform up to t rewrite (that is, delete) steps per cycle.
We focus on the descriptional ...
Preprint
Restarting automata with restricted utilization of auxiliary symbols
(Universität Kassel, FB 17, Mathematik/Informatik, 2005)
The restarting automaton is a restricted model of computation that was introduced by Jancar et al. to model the so-called analysis by reduction, which is a technique used in linguistics to analyze sentences of natural languages. The most general models of restarting automata make use of auxiliary symbols in their rewrite operations, although this ability does not directly correspond to any aspect of the analysis by reduction. Here we put restrictions on the way in which restarting automata use auxiliary symbols, and ...
Preprint
Learning analysis by reduction from positive data
(Universität Kassel, FB 17, Mathematik/Informatik, 2005)
Analysis by reduction is a linguistically motivated method for checking correctness of a sentence. It can be modelled by restarting automata. In this paper we propose a method for learning restarting automata which are strictly locally testable (SLT-R-automata). The method is based on the concept of identification in the limit from positive examples only. Also we characterize the class of languages accepted by SLT-R-automata with respect to the Chomsky hierarchy.
Preprint
Shrinking restarting automata
(Universität Kassel, FB 17, Mathematik/Informatik, 2005)
Restarting automata are a restricted model of computation that was introduced by Jancar et.al. to model the so-called analysis by reduction. A computation of a restarting automaton consists of a sequence of cycles such that in each cycle the automaton performs exactly one rewrite step, which replaces a small part of the tape content by another, even shorter word. Thus, each language accepted by a restarting automaton belongs to the complexity class $CSL cap NP$. Here we consider a natural generalization of this model, ...
Preprint
5. Krypto-Tag - Workshop über Kryptographie
(2006)
Dieser Tagungsband enthält die gesammelten Zusammenfassungen der acht eingereichten Vorträge des 5. Krypto-Tags. Der Kryptotag ist eine zentrale Aktivität der Fachgruppe "Angewandte Kryptologie" der Gesellschaft für Informatik e.V. Er ist eine wissenschaftliche Veranstaltung im Bereich der Kryptologie und von der organisatorischen Arbeit der Fachgruppe getrennt.
Preprint
Efficient data mining based on formal concept analysis
(2002)
Formal Concept Analysis is an unsupervised learning technique for conceptual clustering. We introduce the notion of iceberg concept lattices and show their use in Knowledge Discovery in Databases (KDD). Iceberg lattices are designed for analyzing very large databases. In particular they serve as a condensed representation of frequent patterns as known from association rule mining. In order to show the interplay between Formal Concept Analysis and association rule mining, we discuss the algorithm TITANIC. We show that ...