A user-knowledge crowdsourcing task assignment model and heuristic algorithm for Expert Knowledge Recommendation Systems-Reference-Cited by-同舟云学术

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A user-knowledge crowdsourcing task assignment model and heuristic algorithm for Expert Knowledge Recommendation Systems

Published:2020-11 Issue: Volume:96 Page:103959
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Gao Li,Gan Yi,Zhou Binghai,Dong Mengyu

Funder

Ministry of Education Humanities and Social Sciences Foundation of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference33 articles.

1. Distributed modeling of smart parking system using LSTM with stochastic periodic predictions;Anagnostopoulos;Neural Comput. Appl.,2019

2. Proximity-aware worker preferred task allocation for spatial crowdsourcing;Anto Jaya;Procedia Comput. Sci.,2020

3. General framework, opportunities, and challenges for crowdsourcing techniques: A comprehensive survey;Bhatti;J. Syst. Softw.,2020

4. An investigation of using mobile and situated crowdsourcing to collect annotated travel activity data in real-world settings;Chang;Int. J. Hum.-Comput. Stud.,2017

5. Spatiotemporal modeling for nonlinear distributed thermal processes based on KL decomposition, MLP and LSTM network;Fan;IEEE Access,2020

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3. Rating Distribution-Aware Deep Cognitive Convolution Matrix Factorization for Recommendation Systems;Arabian Journal for Science and Engineering;2024-08-10

4. Research paper classification model based on deep learning network and text fine-grained features;2024-07-19

5. System-of-systems approach to spatio-temporal crowdsourcing design using improved PPO algorithm based on an invalid action masking;Knowledge-Based Systems;2024-02

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