International organization science and technology term topic sentence extraction method driven by multiple machine translation engines

Abstract

The invention discloses an international organization science and technology term topic sentence extraction method based on a multi-machine translation engine, and relates to the technical field of information science and knowledge engineering. According to the method, on the basis of a cross-language term knowledge base, by calling various machine translation engines and adopting a natural language chunk processing technology, the technical steps of automatic term sentence recognition, topic statement chunk analysis, translation connection and fusion and the like of the cross-language science and technology text are designed. Therefore, term knowledge point rapid identification, subject sentence automatic detection and high-quality translation fusion generation are carried out on international organization science and technology knowledge, so that subject sentence extraction accuracy and fluency are guaranteed, finally science and technology information issued by an international organization is dynamically monitored, and the knowledge processing requirement of a user for cross-language professional science and technology knowledge is met.

Description

technical field [0001] The invention relates to the technical fields of information science and knowledge engineering, in particular to a method for extracting topic sentences of scientific and technological terms of international organizations driven by multiple machine translation engines. Background technique [0002] Machine translation, that is, translating text in one language into another by computer, has become one of the important methods to solve the multilingual barrier at present. As early as 2013, Google Translate provided translation services up to one billion times a day, which is equivalent to the annual human translation volume in the world, and the number of words processed is equivalent to one million books. [0003] International organizations have published a large number of professional knowledge documents, which are highly authoritative and rich in knowledge content. However, due to language barriers, it is difficult for domestic users to quickly under...

AI Technical Summary

Problems solved by technology

[0004] Existing machine translation is mainly based on statistical machine translation. Generally, it can translate a single sentence in a general field with high accuracy. However, there are big problems in the translation of professional knowledge such as terminology. Most of them only translate the superficial meaning of the corresponding words. The overall information of the sentence is missing, resulting in insufficient translation accuracy for professional documents

This is also one of the main difficulties of existing machine translation engines, which are difficult to apply to cross-language knowledge discovery and monitoring

The reasons are as follows: First, most of the knowledge content released by international organizations revolves around certain topics in specific professional fields, with many terms, complex sentence structures, and various languages. It is often difficult for a single machine translation engine to handle, and the accuracy plummets; second, from the needs of users From a perspective, it is rarely necessary to rely on machines for full-text translation. The main core task is to quickly integrate topic sentences and professional words to meet the needs of knowledge monitoring

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