Corpus-Based Chinese-Korean Abstracting Translation System

A Corpus-Based Chinese-Korean Abstracting Translation System is designed and imple­ mented. Firstly, a text indexing method called Natural Hierarchical Network(NHN) is intro­ duced, and then a Corpus-Based Word Seg­ mentation algorithm is developed with the segmentation correctness of 98% for open test. Based on a words weighting function and a sentence importance weighting function which can dynamically calculate the importance of words and sentences by using the word fre­ quency both in corpus and context, word length, sentence length and so on, an abstract­ ing system is implemented to produce ab­ stracts of texts in deferent languages and do­ mains by any abstracting rate. Experiments show that generally abstracts produced by 10% to 20% abstracting rates can cover 90% of the important sentences of the input texts. Finally, combines with an Example-Based Chinese-Korean Machine Translation System, the generated abstracts are translated into tar­ get language with the correctness of transla­ tion of more than 70% by the important words oriented machine translation strategy.