Text preprocessing is not only an essential step to prepare the corpus for modeling but also
a key area that directly affects the natural language processing (NLP) application results. For …

Matrix Factorization is a successful approach for generating an effective recommender
system. However, most existing matrix factorization methods suffer from the sparsity and cold …

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

Social network services have become widely used, and hashtags, which are implicitly
involved in delivering specific information, have shown to greatly improve user engagement …

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

Hashtag recommendation aims to suggest hashtags to users to annotate and describe the
key information in the text, or categorize their posts. In recent years, several hashtag …

Tag recommendation is critical in organizing and managing resources on social media
platforms. The incessant deluge of new content and terms and the challenge of creating new …

Large language models (LLM) have recently emerged as a powerful tool for a variety of
natural language processing tasks, bringing a new surge of combining LLM with …

Knowledge graph embedding aims to transform the entities and relations of triplets into the
low-dimensional vectors. Previous methods are oriented towards the static knowledge …

As one of the largest microblogging websites in the world, Twitter generates a huge amount
of information daily. The massive size of the generated data increases the difficulty for …