The matrix factorization model based on user-item rating data has been widely studied and
applied in recommender systems. However, data sparsity, the cold-start problem, and poor …

Social networking platforms have witnessed tremendous growth of textual, visual, audio, and
mix-mode contents for expressing the views or opinions. Henceforth, Sentiment Analysis …

Abstract Syntax parse trees are a method of representing sentence structure and are often
used to provide models with syntax information and enhance downstream task performance …

Abstract As technology advances, Facebook, Twitter, and microblogging sites have become
the most effective platforms for communication and information exchange. Through these …

This paper constructs a novel enhanced latent semantic model based on users' comments,
and employs regularization factors to capture the temporal evolution characteristics of users' …

Sentiment analytics is the process of applying natural language processing and methods for
text-based information to define and extract subjective knowledge of the text. Natural …

This paper focuses on developing semantic image caption generation techniques that
leverage image and scene understanding. More particularly, we are interested in …

Background Tree-structured neural networks have shown promise in extracting lexical
representations of sentence syntactic structures, particularly in the detection of event triggers …

Sentiment analysis of social media texts has become a research hotspot in information
processing. Sentiment analysis methods based on the combination of machine learning and …

Analyzing the semantic similarity of cross-lingual texts is a crucial part of natural language
processing (NLP). The computation of semantic similarity is essential for a variety of tasks …