Recent advances in blockchain and artificial intelligence integration: Feasibility analysis, research issues, applications, challenges, and future work
Blockchain constructs a distributed point‐to‐point system, which is a secure and verifiable
mechanism for decentralized transaction validation and is widely used in financial economy …
mechanism for decentralized transaction validation and is widely used in financial economy …
A novel time-aware food recommender-system based on deep learning and graph clustering
Food recommender-systems are considered an effective tool to help users adjust their
eating habits and achieve a healthier diet. This paper aims to develop a new hybrid food …
eating habits and achieve a healthier diet. This paper aims to develop a new hybrid food …
A deep learning based trust-and tag-aware recommender system
Recommender systems are popular tools used in many applications, such as e-commerce, e-
learning, and social networks to help users select their desired items. Collaborative filtering …
learning, and social networks to help users select their desired items. Collaborative filtering …
TrustDL: Use of trust-based dictionary learning to facilitate recommendation in social networks
Collaborative filtering (CF) is a widely applied method to perform recommendation tasks in a
wide range of domains and applications. Dictionary learning (DL) models, which are highly …
wide range of domains and applications. Dictionary learning (DL) models, which are highly …
Dual-grained human mobility learning for location-aware trip recommendation with spatial–temporal graph knowledge fusion
Trip recommendation is a popular and significant location-aware service that can help
visitors make more accurate travel plans. Its principal purpose is to provide a sequence of …
visitors make more accurate travel plans. Its principal purpose is to provide a sequence of …
HyGate-GCN: Hybrid-Gate-Based Graph Convolutional Networks with dynamical ratings estimation for personalized POI recommendation
The presence of user-generated ratings has dramatically facilitated the development of
recommendation systems to aid users in discovering relevant and personalized points of …
recommendation systems to aid users in discovering relevant and personalized points of …
Prompt-based and weak-modality enhanced multimodal recommendation
Beyond conventional recommendation systems that rely merely on user-item interaction
data, multimodal recommendation systems additionally exploit the item multimodal data for …
data, multimodal recommendation systems additionally exploit the item multimodal data for …
Meta multi-instance multi-label learning by heterogeneous network fusion
Abstract Multi-Instance Multi-Label Learning (MIML) models complex objects (bags), each of
which is composed with a set of instances and associated with a set of labels. Current MIML …
which is composed with a set of instances and associated with a set of labels. Current MIML …
Open knowledge graph completion with negative-aware representation learning and multi-source reliability inference
Multi-source data fusion is essential for building smart cities by providing a comprehensive
and holistic understanding of urban environments. Specifically, smart city-oriented …
and holistic understanding of urban environments. Specifically, smart city-oriented …
Multi-dimensional shared representation learning with graph fusion network for session-based recommendation
Abstract The Session-based Recommendation (SBR) system aims to forecast anonymous
users' short-term decisions. Many prior research have demonstrated that using Graph …
users' short-term decisions. Many prior research have demonstrated that using Graph …