OBJECTIVE: To determine whether the automatic classification of documents can be useful
in systematic reviews on medical topics, and specifically if the performance of the automatic …

With the emergence of social networks and micro-blogs, a huge amount of short textual
documents are generated on a daily basis, for which effective tools for organization and …

Privacy policies have become a focal point of privacy research. With their goal to reflect the
privacy practices of a website, service, or app, they are often the starting point for …

Public procuring entities globally have been adopting the digitised approach in order to
improve efficiency. However, existing systems have been found to be fragmented and …

Technical debt (TD) is a metaphor for code-related problems that arise as a result of
prioritizing speedy delivery over perfect code. Given that the reduction of TDs can have long …

Hubness has been recently identified as a problematic phenomenon occurring in high-
dimensional space. In this paper, we address a different type of hubness that occurs when …

As online texts have been rapidly growing, their automatic classification gains more interest
with machine learning methods. Nevertheless, comparatively few research could be found …

Support Vector Machine model is one of the most intensive used text data classifiers ever
since the moment of its development. However, its performance depends not only on its …

目前对中文文本分类的研究主要集中于对字符粒度, 词语粒度, 句子粒度, 篇章粒度等数据信息的
单一模式划分, 这往往缺少不同粒度下语义所包含的信息特征. 为了更加有效提取文本所要表达 …

This paper presents a comparison of word embeddings in text classification using RNN and
CNN. In the field of image classification, deep learning methods like as RNN and CNN have …