The use of information technology in linguistic research gave rise in the 1950s to what is known as Natural Language Processing, but that framework was created without paying due attention to the need for logical reconstruction of linguistic concepts which were borrowed directly from barely formalised structural linguistics. The Computer-aided Acquisition of Semantic Knowledge project based on the Knowledge Discovery in Databases technology enabled us to interact with computers while gathering and improving our knowledge about languages. Thus, with the help (...) of data mining tools, as a result of revisiting two sorts of generally admitted linguistic theories, we succeeded in improving these local linguistic approaches by proposing to unify the Associative Semantics theory with the Meta-Informative Centering theory. The resulting Distributed Grammar program treats, in addition to the above types of information, the third one, para-information which – despite many studies – had no uniform theoretical background in general linguistics. This DG program aims to lay the foundations for creating the theoretical background of Conceptual Linguistics. (shrink)

Niniejszy artykuł dotyczy modelowania różnych zjawisk przy użyciu pojęć i narzędzi informatycznych, związanych głównie z badaniami nad sztuczną inteligencją (SI). Po przedstawieniu idei sformalizowanego modelu informatycznego (MI) omawiamy ogólnie interaktywną procedurę modelowania (która składa się z czterech, powtarzanych cyklicznie, etapów: abstrakcji, formalizacji, symplifikacji i weryfikacji), a następnie charakteryzujemy ją w kontekście szczególnym, tj informatycznym. Omawiając różne typy MI, odwołujemy się przede wszystkim do badań nad AI; np. rozróżniamy między modelami regułowymi (implementowanymi często w postaci systemów eksperckich), sieciowymi (realizowanymi często w (...) postaci sztucznych sieci neuronowych) oraz ewolucyjnymi (nawiązującymi, na przykład, do teorii algorytmów genetycznych). Co jest jednak najważniejsze, przedstawiamy pogląd, zgodnie z którym różne, przynależne do badań nad AI, techniki automatycznego uczenia się mogą, a w gruncie rzeczy powinny, być stosowane do automatyzacji poszczególnych etapów procedury modelowania. (shrink)

Compared to existing classical approaches to semiotics which are dyadic (signifier/signified, F. de Saussure) and triadic (symbol/concept/object, Ch. S. Peirce), this theory can be characterized as tetradic ([sign/semion]//[object/noema]) and is the result of either doubling the dyadic approach along the semiotic/ordinary dimension or splitting the ‘concept’ of the triadic one into two (semiotic/ordinary). Other important features of this approach are (a) the distinction made between concepts (only functional pairs of extent and intent) and categories (as representations of expressions) and (b) (...) the indication of the need for providing the mathematical passage from the duality between two sets (where one is a singleton) within systems of sets to category-theoretical monoids within systems of categories while waiting for the solution of this problem in the field of logic. Last but not least, human language expressions are the most representative physical instances of semiotic objects. Moreover, as computational experiments which are possible with linguistic objects present a high degree of systematicity (of oppositions), in general, it is relatively easy to elucidate their dependence on the concepts underlying signs. This new semiotic theory or rather this new research program emerged as the fruit of experimentation and reflection on the application of data science tools elaborated within the frameworks of Rough Set Theory (RST), Formal Context Analysis (FCA) and, though only theoretically, Distributed Information Logic (DIL). The semiotic objects (s-objects) of this theory can be described in tabular datasets. Nevertheless, at this stage of formalisation of the theory, lattices (not trees) can be used as working representation structures for characterizing the components of concept systems and graphs for categories of each layer. (shrink)