text_classification_NoReC

Grammar learning has been a bottleneck problem for a long time. In this paper, we propose a method of semantic separator learning, a special case of grammar learning. The method is based on the hypothesis that some classes of words, called semantic separators, split a sentence into several constituents. The semantic separators are represented by words together with their part-of-speech tags and other information so that rich semantic information can be involved. In the method, we first identify t

Text Categorization (TC) is a task of classifying a set of documents into one or more predefined categories. Centroid-based method, a very popular TC method, aims to make classifiers simple and efficient by constructing one prototype vector for each class. It classifies a document into the class that owns the prototype vector nearest to the document. Many studies have been done on constructing prototype vectors. However, the basic philosophies of these methods are quite different from each other

sublime text 是一款实用精巧的简化文本开发工具

Semantic Similarity Analysis between High-Level Model Description Text and Low-Level Implementation Text for Network Survivability

VB 单击text自动出现下拉菜单，如果右键，则Button = 2

VB 复制任何窗体中的文字均出现在text1中

sublime-text-3-config：Sublime Text 3用户软件包和配置

简体中文| 简介 PaddleNLP 2.0具有丰富的模型库，简洁易用的API与高性能的分布式训练的能力，可以为飞轮开发者提升文本建模效率，并提供基于Padddle 2.0的NLP领域最佳实践。 特性 丰富的模型库 涵盖了NLP主流应用相关的前沿模型，包括中文词向量，预训练模型，词法分析，文本分类，文本匹配，文本生成，机器翻译，通用对话，问答系统等，更多详细介绍请查看。 简洁易用的API 深度兼容飞轮2.0的高层API体系，提供可替换的文本建模模块，可大幅度减少数据处理，组网，训练互换的代码开发量，提高文本建模开发效率。 高效分散训练 通过深度优化的混合精度训练策略与舰队分布式训练API，可充

Inspired by the fact that edge is an important cue to distinguish texts from background, we propose a novel scene text detection method via edge cue and multiple features, which has two main parts, i.e. candidate character region (CCR) extraction and region classification. For CCR extraction, the ed