AUTOMATIC SUMMARIZATION MODEL ORIENTED TOWARD AUTOMATIC TRANSLATION (BASED ON THE KNOWLEDGE BASE)

Abstract

The present paper is concerned with a model of automatic summarization for scientific
and technical texts, oriented toward automatic translation. The model consists of
three main components: a keyword extractor, a knowledge base and a summarization algorithm.
The summary text is generated in the form excluding linguistic phenomena that
can cause problems during automatic translation (the syntactic complexity of the sentence
is controlled and its length is limited, ellipsis and long subordinate clauses are not allowed).
Rules for summary generation define the grammar of summary sentences. The
summarization algorithm consists of four top level procedures – preprocessing and analysis
of the article text, summary content selection and summary text generation.