We present the results of experimenting with schemes for learning probabilistic dependency grammars1 for English from corpora labelled with part-of-speech information. We intend our system to produce widecoverage grammars which have some resemblance to the standard 2 context-free grammars of English which grammarians and linguists commonly exhibit as exampies.

The paper demonstrates the efficient use of hybrid intelligent systems for solving the classification problem of bankruptcy. The aim of the study is to obtain classification schemes able to predict business failure. Previous attempts to form efficient classifiers for the same problem using intelligent or statistical techniques are discussed throughout the paper. The application of neural logic ...

This paper describes an algorithm, called SEQUITUR, that identifies hierarchical structure in sequences of discrete symbols and uses that information for compression. On many practical sequences it performs well at both compression and structural inference, producing comprehensible descriptions of sequence structure in the form of grammar rules. The algorithm can be stated concisely in the form...

For surviving in their complex and dynamic environments, organisations should be adaptable and interoperable with these environments. Stakeholders’ expectations change unpredictably and are often dependent on the contextual information. A context sensitive BP model is able to adapt the execution of the instances to the changing contexts and then to the stakeholders’ requirements. Our objective ...

We propose a novel technique of learning how to transform the source parse trees to improve the translation qualities of syntax-based translation models using synchronous context-free grammars. We transform the source tree phrasal structure into a set of simpler structures, expose such decisions to the decoding process, and find the least expensive transformation operation to better model word ...

We study the possibilities to infer pure context-free langauges from positive data. We can show that while the whole class of pure context-free languages is not infer-able from positive data, it has interesting subclasses which have the desired inference property. We study uniform pure languages, i.e., languages generated by pure grammars obeying restrictions on the length of the right hand sid...

The paper describes an extensive experiment in inside-outside estimation of a lexicalized proba-bilistic context free grammar for German verb-final clauses. Grammar and formalism features which make the experiment feasible are described. Successive models are evaluated on precision and recall of phrase markup.

Modular grammatical formalisms provide an essential step towards improved grammar engineering practices. However, as we depart from traditional deterministic models, some intrinsic static checks are lost. The paper shows why grammar verification is necessary for reliable uses of context-free grammars (CFGs) and parsing expression grammars (PEGs) as modular syntax definitions. Simple conservativ...

Context-awareness has emerged as a new perspective for business process modelling. Even though some works have studied it, many challenges have not been addressed yet. There is a clear need for approaches that (i) facilitate the identification of the context properties that influence a business process and (ii) provide guidance for correct modelling of contextualised business processes. This pa...

In this note we show, that the set of valid boolean formulae over a nite set of variables is a natural example for a context-free language. Context-free languages are very important in computer science. Thus it would be nice to enlarge the collection of natural and attractive examples. One interesting example is obtained by the question whether the set of tautologies over a xed nite set of vari...