The aim of this study is to provide an overview the state-of-the-art elements of text
classification. For this purpose, we first select and investigate the primary and recent studies …

Big multimedia data is heterogeneous in essence, that is, the data may be a mixture of
video, audio, text, and images. This is due to the prevalence of novel applications in recent …

文本自动分类是信息检索与数据挖掘领域的研究热点与核心技术, 近年来得到了广泛的关注和
快速的发展. 提出了基于机器学习的文本分类技术所面临的互联网内容信息处理等复杂应用的 …

Efficient distributed numerical word representation models (word embeddings) combined
with modern machine learning algorithms have recently yielded considerable improvement …

In this survey we discuss the task of hierarchical classification. The literature about this field
is scattered across very different application domains and for that reason research in one …

Hierarchical multi-label text classification (HMTC) is a fundamental but challenging task of
numerous applications (eg, patent annotation), where documents are assigned to multiple …

The recent surge in the usage of social media has created an enormous amount of user‐
generated content (UGC). While there are streams of research that seek to mine UGC, these …

Text categorization is a significant tool to manage and organize the surging text data. Many
text categorization algorithms have been explored in previous literatures, such as KNN …

Understanding the parameter estimation of softmax gating Gaussian mixture of experts has
remained a long-standing open problem in the literature. It is mainly due to three …

Automatically categorizing documents into pre-defined topic hierarchies or taxonomies is a
crucial step in knowledge and content management. Standard machine learning techniques …