INTEGRAL FORMAL SEMANTICS AND THE DESIGN OF LEGAL FULL-TEXT DATABASES

It is reported about the development of a new approach to the formaliz ation of communication by means of Natural Language. This approach is called Integral Formal Semantics (IFS). Chief philosophical principles of IFS and the composition are set forth. A number of opportunities a fforded by IFS (by S-languages, T-languages, K-languages) both for des cribing structured meanings of discourses and for representing knowled ge is characterized. In particular, it is shown that the means of IFS permit to approximate main constructions of some modern terminological knowledge representation languages and provide important additional p ossibilities of describing notions. The actuality of developing effect ive formal methods for designing full-text databases, in particular, l egal full-text databases is pointed out. The advantages of applying th e theory of K-calculuses and K-languages (the central constituent of I FS) to the design of full-text databases are stated. These advantages are illustrated on an example showing the possibilities of using K-lan guages in the design of legal full-text databases. Some interconnectio ns of IFS with the main known approaches to the formalization of natur al-language semantics and with cognitive linguistics are described.The conjective is stated that IFS creates the theoretical basis for the d evelopment of a new branch of cybernetics which may be called Mathemat ical Linguocybernetics and which is to be, as concerns the content, a mathematical thory of natural-language communication. The conclusion i s drawn that IFS allows us to go to an entirely new level of mathemati cal studying Natural Language. This new level can be characterized by the possibility to describe structured meanings of practically arbitra ry (very likely, arbitrary) sentences and discourses pertaining to sci ence, technology, business, medicine, law, etc. and by the orientation towards and large prospects of developing models useful for the const ruction or natural-language-processing systems.