Translingual text mining for identification of language pair phenomena
Jolanta Mizera–Pietraszko · 2016
Translingual Text Mining (TTM) is an innovative technology of natural language processing for building multilingual parallel corpora, processing machine translation, contextual knowledge acquisition, information extraction, query profiling, language modeling, contextual word sensing, creating feature test sets and for variety of other purposes. The Keynote Lecture will discuss opportunities and challenges of this computational technology. In particular, the focus will be made on identification of language pair phenomena and their applications to building holistic language model which is a novel tool for processing machine translation, supporting professional translations, evaluation of translingual systems efficiency and also for improving the process of teaching foreign languages regardless of the level of students' proficiency. Some components incorporated to machine translation systems rely specifically on language-pair phenomena like for example language recognizer, or word deliminer. Nowadays, declarative programming is becoming widely used just for describing language pair phenomena by graphical formalism. Translation irreversibility represents a unique language and system independent asymmetrical translation innovative technology, which will be presented during the Keynote lecture.