In e-commerce websites and related micro-blogs, users supply online reviews expressing
their preferences regarding various items. Such reviews are typically in the textual …

With the growth of online information, varying personalization drifts and volatile behaviors of
internet users, recommender systems are effective tools for information filtering to overcome …

Abstract In the Big Data Era, recommender systems perform a fundamental role in data
management and information filtering. In this context, Collaborative Filtering (CF) persists as …

Many multimodal recommender systems have been proposed to exploit the rich side
information associated with users or items (eg, user reviews and item images) for learning …

User reviews contain rich semantics towards the preference of users to features of items.
Recently, many deep learning based solutions have been proposed by exploiting reviews …

Recommendation is an effective marketing tool widely used in the e-commerce business,
and can be made based on ratings predicted from the rating data of purchased items. To …

The widespread use of online recruitment services has led to an information explosion in the
job market. As a result, recruiters have to seek intelligent ways for Person-Job Fit, which is …