Federated recommendation applies federated learning techniques in recommendation
systems to help protect user privacy by exchanging models instead of raw user data …

Federated recommendation systems employ federated learning techniques to safeguard
user privacy by transmitting model parameters instead of raw user data between user …

With the increasing concern about data privacy and data explosion, some encrypted and
compressed key-value (KV) stores have been proposed. A remarkable way to combine …

To address the construction industry's fragmented resources and to facilitate its service-
oriented transformation, a new service paradigm of a construction service trading platform …

Crowdsourcing is an effective technique that allows humans to solve complex problems that
are hard to accomplish by automated tools. Some significant challenges in crowdsourcing …

Submodular maximization is a fundamental problem in many Internet of Things applications,
such as sensor placement, resource allocation, and mobile crowdsourcing. Despite being …

With the rapid development and widespread application of crowdsourcing, the limitations of
traditional systems are gradually exposed. First, traditional systems fail to protect the privacy …

Crowdsourcing is a promising human-in-the-loop paradigm for processing computer hard
tasks by harnessing crowd intelligence. However, canonical crowdsourcing systems mostly …

Blockchain technology has attracted considerable attention due to the boom of
cryptocurrencies and decentralized applications. Among them, the emerging blockchain …

任务分配是群智协同计算和众包中的核心问题之一, 即通过设计合理的任务分配策略,
在满足任务约束条件下, 将群智任务分配给合适的工作者, 以提高群智任务的完成效率和结果 …