With the continuous increment of city volume and size, a number of traffic-related urban units
(eg, vehicles, roads, buildings, etc.) are emerging rapidly, which plays a heavy burden on …

Long short-term memory (LSTM) models provide high predictive performance through their
ability to recognize longer sequences of time series data. More recently, bidirectional deep …

Deep neural networks (DNNs) have been widely applied for detecting COVID-19 in medical
images. Existing studies mainly apply transfer learning and other data representation …

Abstract Cross-Domain Recommendation (CDR) aims to solve data sparsity and cold-start
problems by utilizing a relatively information-rich source domain to improve the …

Personalized recommendation plays a critical role in providing decision-making support for
product and service analysis in the field of business intelligence. Recently, deep neural …

With the advancements of the Health 2.0 technology, large-scale healthcare services are
available online. Recommender systems for healthcare services have emerged for decision …

The large increase in the number of available Web services makes the selection of suitable
services a big challenge. Several methods have been developed to predict the Quality of …

Blockchain technology has the characteristics of decentralization and tamper resistance,
which can store data safely and reduce the cost of trust effectively. However, the existing …

With the wide spread and deepening of service-oriented computing, more and more
enterprises and organizations are constructing their applications by integrating third-party …

With the ever-increasing popularity of Internet of Things (IoT), massive enterprises are
attempting to encapsulate their developed outcomes into various lightweight Web …