基于深度学习的文本挖掘研究

Text Mining Based on In-Depth Learning

随着互联网的快速发展,网络上的文本信息急速增长,如何从庞大的信息库中提取有用的信息就依赖于文本挖掘技术.由于文本挖掘是深度学习中重要的一部分,论文对基于深度学习的文本挖掘研究进行了综述.首先介绍了文本挖掘的过程及应用领域,由此说明了文本挖掘的重要性;其次通过浅层神经网络算法的局限性,说明提出基于深度学习文本挖掘的必要性;然后提出了融合深度学习特征的文本挖掘技术,主要对浅层学习特征、深层学习特征展开介绍;最后总结了深度学习的最新研究进展及对它在文本挖掘的应用进行了综述.

With the rapid development of the Internet and increasing of online text information, text mining technology is becoming indispensable to extracting useful information from large databases. The importance and the research of text mining based on in-depth learning are reviewed in this paper. The process and application field of text mining are first introduced and the limitations of neural networks are analyzed to stress the necessity of text mining. Finally the characteristics of shallow learning and deep learning are illustrated and the latest research achievements of in-depth learning and its application in text mining are reviewed.