Automatic Identification of False Friends in Parallel Corpora: Statistical and Semantic Approach

False friends are pairs of words in two languages that are perceived as similar but have different meanings. We present an improved algorithm for acquiring false friends from sentence-level aligned parallel corpus based on statistical observations of words occurrences and co-occurrences in the parallel sentences. The results are compared with an entirely semantic measure for cross-lingual similarity between words based on using the Web as a corpus through analyzing the words’ local contexts extracted from the text snippets returned by searching in Google. The statistical and semantic measures are further combined into an improved algorithm for identification of false friends that achieves almost twice better results than previously known algorithms. The evaluation is performed for identifying cognates between Bulgarian and Russian but the proposed methods could be adopted for other language pairs for which parallel corpora and bilingual glossaries are available.

Conceptual Idea of Identification of Patterns and Problem Solving in the Human’s Memory and the Possibilities to Use it in Artificial Intelligent

Given cybernetic idea is formed on the basis of neurophysiologic, neuropsychological, neurocybernetic data and verisimilar hypotheses, which fill gaps of formers, of the author as well. First of all attention is focused on general principles of a Memory organization in the brain and processes which take part in it that realize such psychical functions as perception and identification of input information about patterns and a problem solving, which is specified by the input and output conditions, as well. Realization of the second function, essentially cogitative, is discussed in the aspects of figurative and lingual thinking on the levels of intuition and understanding. The reasons of advisability and principles of bionic approach to creation of appropriate tools of artificial intelligent are proposed.

ASPICO: Advanced Scientific Portal for International Cooperation on Digital Cultural Conten

* This research is partially supported by a grant (bourse Lavoisier) from the French Ministry of Foreign Affairs (Ministère des Affaires Etrangères).