Joint modelling of task requirements and worker preferences based on heterogeneous features and multiple interactions for knowledge-intensive crowdsourcing recommendation

IF 1.7 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

International Journal of Bio-Inspired Computation Pub Date : 2023-01-01 DOI:10.1504/ijbic.2023.10056898

Guangzhu Tan, Jiejie Tian, Min Gao, Shuai Zhang, Xu Wang, Biyu Yang, Linda Yang, Jiafu Su

引用次数: 0

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基于异构特征和多重交互的知识密集型众包推荐任务需求和员工偏好联合建模

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Bio-Inspired Computation COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

5.10

自引率

5.70%

发文量

审稿时长

>12 weeks

期刊介绍： IJBIC discusses the new bio-inspired computation methodologies derived from the animal and plant world, such as new algorithms mimicking the wolf schooling, the plant survival process, etc. Topics covered include: -New bio-inspired methodologies coming from creatures living in nature artificial society- physical/chemical phenomena- New bio-inspired methodology analysis tools, e.g. rough sets, stochastic processes- Brain-inspired methods: models and algorithms- Bio-inspired computation with big data: algorithms and structures- Applications associated with bio-inspired methodologies, e.g. bioinformatics.