文本特征提取的研究进展

Research progress on text feature extraction

文本理解是人工智能的一个重要分支,其技术推动了人与计算机之间在自然语言上的有效交互.为了让计算机准确地理解和感知文本数据,文本特征提取是最为基础和关键的步骤之一.基于此,本文介绍文本特征提取研究的发展历史,以及近年来主流特征提取的方法,并对未来的研究方向进行展望.首先,介绍语义最底层的词级表示;接着,总结在词级表示基础上衍生出的句级表示上的研究进展;随后,介绍比词级表示和句级表示更高层的篇分析;最后,通过文本特征提取的一个典型应用——问答系统的介绍,阐述文本特征提取的最新方法和技术在问答系统上的应用,并对未来的研究方向做了展望.

Text understanding is an important research branch in artificial intelligence,which avails the effective interaction between human and computer with natural language.Text feature extraction is one of the basic and key steps for computers to understand and perceive the textual data.In this paper,we introduce the development history of text feature extraction and the mainstream feature extraction methods in recent years,and prospects the future research directions of text feature extraction.The three semantic hierarchies,namely word representation,sentence representation and discourse relationship mining are elaborated,then a case is given to show the typical application of text feature extraction on question answering system.