AI-based fog and edge computing: A systematic review, taxonomy and future directions
Resource management in computing is a very challenging problem that involves making
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …
Categorization of knowledge graph based recommendation methods and benchmark datasets from the perspectives of application scenarios: A comprehensive …
Recommender Systems (RS) are established to deal with the preferences of users to
enhance their experience and interest in innumerable online applications by streamlining …
enhance their experience and interest in innumerable online applications by streamlining …
Similarity attributed knowledge graph embedding enhancement for item recommendation
Abstract Knowledge Graph Embedding (KGE)-enhanced recommender systems are
effective in providing accurate and personalized recommendations in diverse application …
effective in providing accurate and personalized recommendations in diverse application …
A semi-supervised matrixized graph embedding machine for roller bearing fault diagnosis under few-labeled samples
Exploring historical measurement data-driven health monitoring schemes for roller bearings
is a current research hotspot. In engineering practice, the type of fault data obtained is often …
is a current research hotspot. In engineering practice, the type of fault data obtained is often …
Guest Editorial: Special section on 5G edge computing-enabled internet of medical things
SHA Shah, D Koundal, V Sai… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The relationship between computing and healthcare has a long history, but adoption of
telemedicine is gradual due to political resistance, lack of infrastructure development …
telemedicine is gradual due to political resistance, lack of infrastructure development …
A Semi-supervised Sensing Rate Learning based CMAB scheme to combat COVID-19 by trustful data collection in the crowd
The recruitment of trustworthy and high-quality workers is an important research issue for
MCS. Previous studies either assume that the qualities of workers are known in advance, or …
MCS. Previous studies either assume that the qualities of workers are known in advance, or …
Graph representation learning with adaptive metric
Contrastive learning has been widely used in graph representation learning, which extracts
node or graph representations by contrasting positive and negative node pairs. It requires …
node or graph representations by contrasting positive and negative node pairs. It requires …
Collaborative meta-path modeling for explainable recommendation
Although recommender systems have achieved considerable success, sometimes it is
difficult to convince users due to the failure to explain the recommendation results. For this …
difficult to convince users due to the failure to explain the recommendation results. For this …
A bi-directional recommender system for online recruitment
Most existing recommendation research has been concentrated on unidirectional
recommendation, ie only recommending items to users. However, in many real-world …
recommendation, ie only recommending items to users. However, in many real-world …
Document-level relation extraction with global and path dependencies
W Jia, R Ma, L Yan, W Niu, Z Ma - Knowledge-Based Systems, 2024 - Elsevier
Document-level relation extraction (RE) focuses on extracting relations for each entity pair in
the same sentence or across different sentences of a document. Several existing …
the same sentence or across different sentences of a document. Several existing …