One of the main benefits of unsupervised learning is that there is no need for labelled data.
As a method of this category, latent Dirichlet allocation (LDA) estimates the semantic …

Predicting the nature of each urban functional region based on the transfer rate of empty
cars plays a crucial role in constructing smart cities and urban planning. The transfer rate of …

In this paper, we propose a generative model named the author-topic-community (ATC)
model for representing a corpus of linked documents. The ATC model allows each author to …

Sentiment analysis has the potential to significantly impact several fields, such as trade,
politics, and opinion extraction. Topic modeling is an intriguing concept used in emotion …

Complex networks provide a powerful way to represent complex systems and have been
widely studied during the past several years. One of the most important tasks of network …

Topic modeling has become a widely used tool for document management. However, there
are few topic models distinguishing the importance of documents on different topics. In this …

Latent community discovery that combines links and contents of a text-associated network
has drawn more attention with the advance of social media. Most of the previous studies aim …

In recent years, social botnets have become a major security threat to both online social
networking websites and their users. Social bots communicate over probabilistically …

With the increasing availability of online scholarly databases, publication records can be
easily extracted and analysed. Researchers can promptly keep abreast of others' scientific …

Online community detection is essential for social network analysis. Modularity is a quality
function used to measure the strength of the community structure discovered with social …