The most important information about the content of a document is represented by the key phrases of that document. In this study an automatic key phrase extraction algorithm is devised using machine learning technique. The proposed method not only considers the document level statistics like TFxIDF, the linguistic features of the phrases are also incorporated. Experiment has been performed on N...

This work proposes a new method in order to simplify linguistic knowledge bases. The main goal consists of improving simultaneously accuracy and interpretability when it is possible, or at least ensuring a good tradeoff between them, as well as consistency of the final knowledge base. It is used with linguistic rules which can be defined by expert, induced from data, or both of them. The simpli...

An important step in the development of systems that require deeper knowledge (e.g., systems that might ultimately infer person-person relationships, event-event relationships, sentiment, and other important information about the world) is the mapping between linguistic annotations that have been developed by researchers and the knowledge objects that might be derived from those linguistic anno...

Parallel corpora encode extremely valuable linguistic knowledge, the revealing of which is facilitated by the recent advances in multilingual corpus linguistics. The linguistic decisions made by the human translators in order to faithfully convey the meaning of the source text can be traced and can bring evidence on linguistic facts which in a monolingual context might be overlooked by a comput...

A semi-automatic procedure of linguistic knowledge acquisition is proposed, which combines corpus-based techniques with the conventional rule-based approach. The rule-based component generates all the possible hypotheses of defects which the existing linguistic knowledge might contain, when it fails to parse a sentence. The rule-based component does not try to identify the defects, but generate...

Improving accuracy in Information Retrieval tasks via semantic information is a complex problem characterized by three main aspects: the document representation model, the similarity estimation metric and the inductive algorithm. In this paper an original kernel function sensitive to external semantic knowledge is defined as a document similarity model. This semantic kernel was tested over a te...

pd The work in this thesis has been carried out under the auspices of the Beha-vioral and Cognitive Neurosciences (BCN) research school, Groningen, and has been part of the Pionier project Algorithms for Linguistic Processing, supported by grant number 220-70-001 from the Netherlands Organisation for Scientific Research (NWO). Acknowledgements As with every PhD project, even though there is but...

The paper deals with an idea of a linguistic knowledge representation and a linguistic inference. Relational linguistic fuzzy model with weights of rules is utilising. The probability of linguistic values of antecedent and consequent variables, calculated according to Zadeh’s definition, is proposed to formulate a linguistic fuzzy model of a stochastic system. The linguistic inference procedure...

We address the question of how previously acquired linguistic knowledge facilitates perception and learning of a new language. We report results from two experiments showing evidence that participants better discriminate a segmental duration contrast in a novel language if they had some previous exposure to a language that uses duration contrastively. Crucially, the perceptual advantage occurs ...