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This introductory tutorial describes a strictly corpus-driven approach for uncovering indications for aspects of use of lexical items. These aspects include ‘(lexical) meaning’ in a very broad sense and involve different dimensions, they are established in and emerge from respective discourses. Using data-driven mathematical-statistical methods with minimal (linguistic) premises, a word’s usage spectrum is summarized as a collocation profile. Self-organizing methods are applied to visualize the complex similarity structure spanned by these profiles. These visualizations point to the typical aspects of a word’s use, and to the common and distinctive aspects of any two words.
This paper presents ongoing research which is embedded in an empirical-linguistic research program, set out to devise viable research strategies for developing an explanatory theory of grammar as a psychological and social phenomenon. As this phenomenon cannot be studied directly, the program attempts to approach it indirectly through its correlates in language corpora, which is justified by referring to the core tenets of Emergent Grammar. The guiding principle for identifying such corpus correlates of grammatical regularities is to imitate the psychological processes underlying the emergent nature of these regularities. While previous work in this program focused on syntagmatic structures, the current paper goes one step further by investigating schematic structures that involve paradigmatic variation. It introduces and explores a general strategy by which corpus correlates of such structures may be uncovered, and it further outlines how these correlates may be used to study the nature of the psychologically real schematic structures.
A topic in the field of knowledge acquisition is the reuse of components that are described at the knowledge level. Problems concern the description, indexing and retrieval of components. In our case there is the additional feature of integrating so called automated building blocks in a knowledge level description. This paper describes what knowledge level descriptions of components for reuse should look like, and proposes a way to describe assumptions and requirements that are to be made explicit. In the paper an extension of the “normal” knowledge acquisition setting is made in the direction of machine learning components.
A library of software components should be essentially more than just a juxtaposition of its items. For problem-solving methods the notion of a family is suggested as means to cluster the items and to provide partially a structure of the library. This paper especially investigates how the similar control flows of the members of such a family can be described in one framework.
Kontexte und ihre Verteilung
(2018)
Die typischen sprachlichen Kontexte, in denen ein Wort verwendet wird, spannen den Rahmen auf, über den sowohl Sprecher als auch Forscher einer Sprache wesentliche Aspekte der Bedeutung des Wortes erschließen und vermitteln. Über große Korpora und entsprechende korpus-, aber auch computerlinguistische Methoden stehen nunmehr systematische Zugänge zu den typischen Verwendungsweisen zur Verfügung, am Institut für Deutsche Sprache etwa über die Kookkurrenzanalyse seit 1995. Auf den Ergebnissen des letztgenannten Verfahrens operieren weitere Methoden, die Bedeutungsbeziehungen zwischen Wörtern auf Ähnlichkeitsbeziehungen des Kontextverhaltens zurückfuhren. In jüngerer Zeit werden Ansätze vor allem aus der Computerlinguistik und dem information retrieval diskutiert, die mit einem ähnlichen Ziel antreten. Dieser Beitrag soll einen prinzipiellen Überblick bieten, wie die verschiedenen Forschungsstränge den Begriff Kontext interpretieren, wie sie ihn systematisch erfassen und zum Vergleich einsetzen. Neben Bedeutungsnähe wird vor allem Mehrdeutigkeit besondere Beachtung finden.
New KARL (Knowledge Acquisition and Representation Language) allows to specify all parts of a problem-solving method (PSM). It is a formal language with a well-defined semantics and thus allows to represent PSMs precisely and unambiguously yet abstracting from implementation detail. In this paper it is shown how the language KARL has been modified and extended to New KARL to better meet the needs for the representation of PSMs. Based on a conceptual structure of PSMs new language primitives are introduced for KARL to specify such a conceptual structure and to support the configuration of methods. An important goal for this extension was to preserve three important properties of KARL: to be (i) a conceptual, (ii) a formal, and (iii) an executable language.