Text classification is the process of automatically tagging a textual document with the most relevant set of labels. This work aims to automatically map an input document based on its vocabulary features to multiple tags. To achieve this goal, a large dataset has been constructed from various ...
There exist a range of hierarchical text classification approaches that classify text documents into a pre-constructed hierarchy of categories. In these approaches, feature selections are often based on terms (words or phrases), which are unsuitable for hierarchically classifying news articles. Named ...
Text classification Text classification is the task of assigning a sentence or document an appropriate category. The categories depend on the chosen dataset and can range from topics. AG News The AG News corpus consists of news articles from the AG’s corpus of news articles on the web ...
Research on Text Classification of Online News 作者:Yibo Xie 来源:Master of Engineering, Master, 华中师范大学, 2022. 新闻文本分类 BERT模型 注意力机制 标签嵌入摘要 自然语言处理(Natural Language Processing,NLP)是当今计算机研究中比较热门和重要的方向之一。文本分类作为NLP的基础任务,其目的是通过对文本内容...
However, with the increasing interest in the area of text classification, we need the most recent systematic overview to better understand what has been achieved in this field. In this study, we aim to overcome the difficulties mentioned above. Moreover, the article presents a latest and ...
We propose in this paper a new online Arabic corpus of news articles, named ANT Corpus, which is collected from RSS Feeds. Each document represents an article structured in the standard XML TREC format. We use the ANT Corpus for Text Classification (TC) by applying the SVM and Naive Bayes...
In both binary and multiclass settings, each document belongs to exactly one class from C, where C is the set of all possible classes. In multilabel classification, a document can have one or more labels/classes attached to it. For example, a news article on a soccer match may belong ...
Keywords:Chinese news text classification; word2vec model; improved TF-IDF; combined-convolutional neural network; public opinion news 1 Introduction 1.1 Research Background and Significance The rapid development of the Internet heralds the arrival of the big data era. The wide application and rapid ...
classification of web news by building a large-scale news annotation dataset and combining deep learning algorithms to train high-quality text classification models [1]. It is worth noting that although such schemes can accurately solve the problem of automatic classification of news text, there are...
Email classification: Classifying emails as spam or non-spam (ham) based on their content. News article classification: Categorizing news articles based on their topics such as politics, entertainment, pop culture, etc. Language identification: Determining the language of a given text. Toxicity classi...