帮我润色下面一段话：信息抽取技术主要分为监督算法抽取和无监督算法抽取有监督算法标注成本高易存在过拟合现象所以近年来无监督算法逐渐成为研究的热点。现有的无监督算法在信息抽取方面存在以下不足：一是抽取的文本信息主要从关键词角度考虑忽视了词语的信息类型且关键词在综合词语的特征方面存在不足；二是文本类别区分度低缺少物流文本分类的相关模型。

Information extraction technology can be broadly classified into two types: supervised algorithm extraction and unsupervised algorithm extraction. While supervised algorithms are effective, their high cost of annotation and the risk of overfitting have led researchers to focus on unsupervised algorithms in recent years. However, current unsupervised algorithms have their own limitations when it comes to information extraction. Firstly, they tend to focus only on the keywords in the text and ignore the type of information conveyed by individual words, leading to a lack of comprehensive features in the extracted data. Secondly, there is a dearth of models for distinguishing between different types of texts, particularly in the field of logistics, which limits the ability of these algorithms to accurately classify texts.