Influenced by the great success of deep learning in computer vision and language
understanding, research in recommendation has shifted to inventing new recommender …

Attention is an important mechanism that can be employed for a variety of deep learning
models across many different domains and tasks. This survey provides an overview of the …

Attention Model has now become an important concept in neural networks that has been
researched within diverse application domains. This survey provides a structured and …

Precise user and item embedding learning is the key to building a successful recommender
system. Traditionally, Collaborative Filtering (CF) provides a way to learn user and item …

Social recommendation has emerged to leverage social connections among users for
predicting users' unknown preferences, which could alleviate the data sparsity issue in …

With the emergence of personality computing as a new research field related to artificial
intelligence and personality psychology, we have witnessed an unprecedented proliferation …

Social recommender systems (SRS) aim to study how social relations influence users'
choices and how to use them for better learning users embeddings. However, the diversity of …

Multimedia recommendation forms a personalized ranking task with multimedia content
representations which are mostly extracted via generic encoders. However, the generic …

Recommending suitable exercises to students in an online education system is highly
useful. Existing approaches usually rely on machine learning techniques to mine large …

Micro-videos have recently gained immense popularity, sparking critical research in micro-
video recommendation with significant implications for the entertainment, advertising, and e …