A Multilingual Algorithm of Texts’ Semantic-Syntactic Analysis for Adaptive Planning Systems
The natural language texts (NL-texts) from the newspapers, e-mail lists, various blogs, etc. are the important sources of information being able to stimulate the elaboration of a new plan of actions. The paper describes a new formal approach to developing multilingual algorithms of semantic-syntactic analysis of NL-texts. It is a part of the theory of K-representations - a new theory of designing semantic-syntactic analyzers of NL-texts with the broad use of formal means for representing input, intermediary, and output data. The current version of the theory is set forth in a monograph published by Springer in 2010. One of the principal constituents of this theory is a complex, strongly structured algorithm SemSynt1 carrying out semantic-syntactic analysis of texts from some practically interesting sublanguages of the English, German, and Russian languages. An important feature of this algorithm is that it doesn’t construct any syntactic representation of the inputted NL-text but directly finds semantic relations between text units. The other distinguished feature is that the algorithm is completely described with the help of formal means, that is why it is problem independent and doesn’t depend on a programming system. The peculiarities and some central procedures of the algorithm SemSynt1 are analyzed.