With the increasing abundance of information resources and the development of deep
learning techniques, recommender systems (RSs) based on deep learning have gradually …

Users from different cultures and backgrounds often feel comfortable expressing their
thoughts on trending topics by generating content in their regional languages. Recently …

Hashtag recommendation suggests hashtags to users while they write microblogs in social
media platforms. Although researchers have investigated various methods and factors that …

This paper addresses the hashtag recommendation problem using high average-utility
pattern mining. We introduce a novel framework called PM-HRec (Pattern Mining for …

The existing models for multi-modal fake news detection focus mainly on capturing common
similar semantics between different modalities to improve detection performance. However …

Hashtag is an iconic feature to retrieve the hot topics of discussion on Twitter or other social
networks. This paper incorporates the pattern mining approaches to improve the accuracy of …

Extracting useful knowledge from multimodal data is the core of many multimedia
applications, such as recommendation systems, and cross-modal retrieval. In this paper, we …

In this paper, we focus on the popularity prediction for marketer-generated content (MGC),
which has not been investigated by current studies. To address this problem, we propose a …

In the real-world social networks, hashtags are widely applied for understanding the content
of an individual microblog. However, users do not always take the initiative in attaching …

In the current matrix factorization recommendation approaches, the item and the user latent
factor vectors are with the same dimension. Thus, the linear dot product is used as the …