Relying on the reform of the learning field curriculum system of ideological and political
education courses in colleges and universities, the association rules between data mining …

Dealing with relational data always required significant computational resources, domain
expertise and task-dependent feature engineering to incorporate structural information into a …

Research and education in machine learning requires diverse, representative, and open
datasets that contain sufficient samples to handle the necessary training, validation, and …

As its number of users increases, TikTok needs to focus on user retention. One such effort
involves answering educational needs through social media. The purpose of this study is to …

Authors are often influenced by historical experience and personal habits when selecting
keywords in composing papers, and tend to choose specific keywords, resulting in a …

This paper comparatively studies people's opinions on AI privacy between the US and
China. Based on data collected from Twitter and Weibo, we perform text clustering and …

Due to the exponential increase in research papers on a daily basis, finding and accessing
related academic documents over the Internet is monotonous. One of the leading …

In this paper, we study the problem of predicting collaborations in co-authorship network. We
formulated our task in terms of link prediction problem on weighted co-authorship network, in …

In this paper, we study the problem of predicting quantity of collaborations in co-authorship
network. We formulated our task in terms of link prediction problem on weighted co …

To enable a quick and accurate access of targeted scientific and technological literature
from massive stocks, here a deep content-based collaborative filtering method, namely …