Peicong He, Yang Xin^*, Yixian Yang

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3067-3084, 2024, DOI:10.32604/cmc.2024.054777 - 15 August 2024

Abstract The proliferation of intelligent, connected Internet of Things (IoT) devices facilitates data collection. However, task workers may be reluctant to participate in data collection due to privacy concerns, and task requesters may be concerned about the validity of the collected data. Hence, it is vital to evaluate the quality of the data collected by the task workers while protecting privacy in spatial crowdsourcing (SC) data collection tasks with IoT. To this end, this paper proposes a privacy-preserving data reliability evaluation for SC in IoT, named PARE. First, we design a data uploading format using blockchain More >

Tianyu Wang^1,2, Kongyang Chen^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2297-2314, 2024, DOI:10.32604/cmes.2024.049964 - 08 July 2024

Abstract Crowdsourcing holds broad applications in information acquisition and dissemination, yet encounters challenges pertaining to data quality assessment and user reputation management. Reputation mechanisms stand as crucial solutions for appraising and updating participant reputation scores, thereby elevating the quality and dependability of crowdsourced data. However, these mechanisms face several challenges in traditional crowdsourcing systems: 1) platform security lacks robust guarantees and may be susceptible to attacks; 2) there exists a potential for large-scale privacy breaches; and 3) incentive mechanisms relying on reputation scores may encounter issues as reputation updates hinge on task demander evaluations, occasionally lacking… More >

Kai Wei¹, Song Yu², Qingxian Pan^1,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 607-622, 2024, DOI:10.32604/cmc.2024.048240 - 25 April 2024

Abstract Crowdsourcing technology is widely recognized for its effectiveness in task scheduling and resource allocation. While traditional methods for task allocation can help reduce costs and improve efficiency, they may encounter challenges when dealing with abnormal data flow nodes, leading to decreased allocation accuracy and efficiency. To address these issues, this study proposes a novel two-part invalid detection task allocation framework. In the first step, an anomaly detection model is developed using a dynamic self-attentive GAN to identify anomalous data. Compared to the baseline method, the model achieves an approximately 4% increase in the F1 value More >

Yu Li, Mingxiao Li, Dongyang Ou^*, Junjie Guo, Fangyuan Pan

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 893-909, 2024, DOI:10.32604/cmes.2023.031350 - 30 December 2023

Abstract With the rapid development of mobile Internet, spatial crowdsourcing has become more and more popular. Spatial crowdsourcing consists of many different types of applications, such as spatial crowd-sensing services. In terms of spatial crowd-sensing, it collects and analyzes traffic sensing data from clients like vehicles and traffic lights to construct intelligent traffic prediction models. Besides collecting sensing data, spatial crowdsourcing also includes spatial delivery services like DiDi and Uber. Appropriate task assignment and worker selection dominate the service quality for spatial crowdsourcing applications. Previous research conducted task assignments via traditional matching approaches or using simple… More > Graphic Abstract

Zhifang Liao¹, Hao Gu¹, Shichao Zhang¹, Ronghui Mo¹, Yan Zhang^2,*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 599-618, 2023, DOI:10.32604/iasc.2023.036794 - 29 April 2023

Abstract Context-Sensitive Task (CST) is a complex task type in crowdsourcing, such as handwriting recognition, route plan, and audio transcription. The current result inference algorithms can perform well in simple crowdsourcing tasks, but cannot obtain high-quality inference results for CSTs. The conventional method to solve CSTs is to divide a CST into multiple independent simple subtasks for crowdsourcing, but this method ignores the context correlation among subtasks and reduces the quality of result inference. To solve this problem, we propose a result inference algorithm based on the Partially ordered set and Tree augmented naive Bayes Infer… More >

Yihuai Liang, Yan Li, Byeong-Seok Shin^*

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2825-2842, 2021, DOI:10.32604/cmc.2021.016682 - 06 May 2021

Abstract A centralized trusted execution environment (TEE) has been extensively studied to provide secure and trusted computing. However, a TEE might become a throughput bottleneck if it is used to evaluate data quality when collecting large-scale data in a crowdsourcing system. It may also have security problems compromised by attackers. Here, we propose a scheme, named dTEE, for building a platform for providing distributed trusted computing by leveraging TEEs. The platform is used as an infrastructure of trusted computations for blockchain-based crowdsourcing systems, especially to securely evaluate data quality and manage remuneration: these operations are handled… More >

Weijin Jiang^1,2, Xiaoliang Liu^1,2,*, Dejia Shi¹, Junpeng Chen^1,2, Yongxia Sun^1,2, Liang Guo³

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1769-1784, 2021, DOI:10.32604/cmc.2021.016609 - 13 April 2021

Abstract Crowd-Sensing is an innovative data acquisition method that combines the perception of mobile devices with the idea of crowdsourcing. It is a new application mode under the development of the Internet of Things. The perceptual data that mobile users can provide is limited. Multiple crowdsourcing parties will share this limited data, but the cost that the crowdsourcing party can pay is limited, and enough mobile users are needed to complete the perceptual task, making the group wisdom is really played. In this process, there is bound to be a game between the crowds and the… More >

Zhifang Liao¹, Xin Xu¹, Peng Lan¹, Liu Yang¹, Yan Zhang², Xiaoping Fan^3,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1379-1396, 2021, DOI:10.32604/cmc.2020.011995 - 26 November 2020

Abstract In the context of the continuous development of the Internet, crowdsourcing has received continuous attention as a new cooperation model based on the relationship between enterprises, the public and society. Among them, a reasonably designed recommendation algorithm can recommend a batch of suitable workers for crowdsourcing tasks to improve the final task completion quality. Therefore, this paper proposes a crowdsourcing recommendation framework based on workers’ influence (CRBI). This crowdsourcing framework completes the entire process design from task distribution, worker recommendation, and result return through processes such as worker behavior analysis, task characteristics construction, and cost… More >

Jinlin Wang¹, Xing Wang^{1, *}, Yuchen Yang¹, Hongli Zhang¹, Binxing Fang¹

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1053-1075, 2020, DOI:10.32604/cmc.2020.08675

Abstract Web information system (WIS) is frequently-used and indispensable in daily social life. WIS provides information services in many scenarios, such as electronic commerce, communities, and edutainment. Data cleaning plays an essential role in various WIS scenarios to improve the quality of data service. In this paper, we present a review of the state-of-the-art methods for data cleaning in WIS. According to the characteristics of data cleaning, we extract the critical elements of WIS, such as interactive objects, application scenarios, and core technology, to classify the existing works. Then, after elaborating and analyzing each category, we More >

Joseph J. Knadler¹, Daniel J. Penny¹, Tyler H. Harris², Gary D. Webb³, Antonio G. Cabrera^1,4, William B. Kyle¹

Congenital Heart Disease, Vol.13, No.5, pp. 794-798, 2018, DOI:10.1111/chd.12669

Abstract Objective: The growing body of medical literature in pediatric cardiology has made it increasingly difficult for individual providers to stay abreast of the most current, meaningful articles to help guide practice. Crowdsourcing represents a collaborative process of obtaining information from a large group of individuals, typically from an online or web‐based community, and could serve a potential mechanism to pool indi‐ vidual efforts to combat this issue. This study aimed to utilize crowdsourcing as a novel way to generate a list of the most relevant, current publications in congenital heart disease, utilizing input from an international… More >