Deep learning has emerged as a powerful machine learning technique that learns multiple
layers of representations or features of the data and produces state‐of‐the‐art prediction …

Nowadays, with the increasing number of Web 2.0 tools, users generate huge amounts of
data in an enormous and dynamic way. In this regard, the sentiment analysis appeared to be …

We describe a novel, multi-task recommendation model, which jointly learns to perform
rating prediction and recommendation explanation by combining matrix factorization, for …

Key to recommender systems is learning user preferences, which are expressed through
various modalities. In online reviews, for instance, this manifests in numerical rating, textual …

Automatic detection of persuasion in online discussion is key to understanding how social
media is used. Predicting persuasiveness is difficult, however, due to the need to model …

We address personalized review summarization, which generates a condensed summary
for a user's review, accounting for his preference on different aspects or his writing style. We …

Generating long and informative review text is a challenging natural language generation
task. Previous work focuses on word-level generation, neglecting the importance of topical …

Understanding contrastive opinions is a key component of argument generation. Central to
an argument is the claim, a statement that is in dispute. Generating a counter-argument then …

Structured sentiment analysis is a newly proposed task, which aims to summarize the overall
sentiment and opinion status on given texts, ie, the opinion expression, the sentiment …

Automatic sentiment analysis can support revealing a subject's emotional state and opinion
tendency toward an entity. In this paper, we present our solutions for the MuSe-Wild sub …