We propose the framework of a Machine Translation (MT) bootstrapping method by using multilingual Wikipedia articles. This novel method can simultaneously generate a statistical machine translation (SMT) and a sentence-aligned corpus. In this study, we perform two types of experiments. The aim of the first type of experiments is to verify the sentence alignment performance by comparing the prop...

With the development of artificial intelligence, more and people hope that computers can understand human language through natural technology, learn to think like beings, finally replace beings complete highly difficult tasks with cognitive ability. As key technology understanding, sentence representation reasoning mainly focuses on method model. Although performance has been improved, there ar...

This paper describes a technique of question type identification for multi-sentence queries in open domain question-answering. Based on observations of queries in real question-answering services on the Web, we propose a method to decompose a multi-sentence query into question items and to identify their question types. The proposed method is an efficient sentence-chunking based technique by us...

This paper proposes an effective method to extract salient sentences using contextual information and statistical approaches for Text Summarization. The proposed method combines two consecutive sentences into a bi-gram pseudo sentence so that contextual information is applied to statistical sentence-extraction techniques. Salient bigram pseudo sentences are first selected by the statistical sen...