Random forest is one of the most widely used machine learning algorithms. Decision trees
used to construct the random forest may have low classification accuracies or high …

In this paper, we make a comparative study of the effectiveness of ensemble technique for
sentiment classification. The ensemble framework is applied to sentiment classification …

The combination between online social networks (OSN) and decision processes provides a
favorable social data analysis paradigm for efficient decision support and business …

Short texts are everywhere in the Web, including messages posted in social media, status
messages and blog comments, and uncovering the topics of this type of messages is crucial …

The process of Web service discovery identifies the most relevant services to requesters'
service queries. We propose a new measure of semantic similarity integrating multiple …

Recently, social network has been paid more and more attention by people. Inaccurate
community detection in social network can provide better product designs, accurate …

With the development of social networking applications, microblog has turned to be an
indispensable online communication network in our daily life. For microblog users …

For effective multi-document summarization, it is important to reduce redundant information
in the summaries and extract sentences, which are common to given documents. This paper …

With the rapid growth of information on the Internet and electronic government recently,
automatic multi-document summarization has become an important task. Multi-document …

Nowadays short texts can be widely found in various social data in relation to the 5G-
enabled Internet of Things (IoT). Short text classification is a challenging task due to its …