Heterogeneous information network embedding for recommendation
Due to the flexibility in modelling data heterogeneity, heterogeneous information network
(HIN) has been adopted to characterize complex and heterogeneous auxiliary data in …
(HIN) has been adopted to characterize complex and heterogeneous auxiliary data in …
Social networks and information retrieval, how are they converging? A survey, a taxonomy and an analysis of social information retrieval approaches and platforms
MR Bouadjenek, H Hacid, M Bouzeghoub - Information Systems, 2016 - Elsevier
There is currently a number of research work performed in the area of bridging the gap
between Information Retrieval (IR) and Online Social Networks (OSN). This is mainly done …
between Information Retrieval (IR) and Online Social Networks (OSN). This is mainly done …
From zero-shot learning to cold-start recommendation
Zero-shot learning (ZSL) and cold-start recommendation (CSR) are two challenging
problems in computer vision and recommender system, respectively. In general, they are …
problems in computer vision and recommender system, respectively. In general, they are …
Key crowdsourcing technologies for product design and development
Traditionally, small and medium enterprises (SMEs) in manufacturing rely heavily on a
skilled, technical and professional workforce to increase productivity and remain globally …
skilled, technical and professional workforce to increase productivity and remain globally …
Fairness among new items in cold start recommender systems
This paper investigates recommendation fairness among new items. While previous efforts
have studied fairness in recommender systems and shown success in improving fairness …
have studied fairness in recommender systems and shown success in improving fairness …
Pp-rec: News recommendation with personalized user interest and time-aware news popularity
Personalized news recommendation methods are widely used in online news services.
These methods usually recommend news based on the matching between news content …
These methods usually recommend news based on the matching between news content …
A survey of trust management systems for online social communities–trust modeling, trust inference and attacks
Trust can help participants in online social communities to make decisions; however, it is a
challenge for systems to map trust into computational models because of its subjective …
challenge for systems to map trust into computational models because of its subjective …
Recommendation for new users and new items via randomized training and mixture-of-experts transformation
The cold start problem is a long-standing challenge in recommender systems. That is, how
to recommend for new users and new items without any historical interaction record? Recent …
to recommend for new users and new items without any historical interaction record? Recent …
Hyper: A flexible and extensible probabilistic framework for hybrid recommender systems
As the amount of recorded digital information increases, there is a growing need for flexible
recommender systems which can incorporate richly structured data sources to improve …
recommender systems which can incorporate richly structured data sources to improve …
Boosting deep CTR prediction with a plug-and-play pre-trainer for news recommendation
Understanding news content is critical to improving the quality of news recommendation. To
achieve this goal, recent studies have attempted to apply pre-trained language models …
achieve this goal, recent studies have attempted to apply pre-trained language models …