首页|Recommendation of Crowdsourcing Tasks Based on Word2vec Semantic Tags

Recommendation of Crowdsourcing Tasks Based on Word2vec Semantic Tags

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  • NSTL
  • Wiley-Hindawi
Crowdsourcing is the perfect show of collective intelligence, and the key of finishing perfectly the crowdsourcing task is to allocate the appropriate task to the appropriate worker. Now the most of crowdsourcing platforms select tasks through tasks search, but it is short of individual recommendation of tasks. Tag-semantic task recommendation model based on deep learning is proposed in the paper. In this paper, the similarity of word vectors is computed, and the semantic tags similar matrix database is established based on the Word2vec deep learning. The task recommending model is established based on semantic tags to achieve the individual recommendation of crowdsourcing tasks. Through computing the similarity of tags, the relevance between task and worker is obtained, which improves the robustness of task recommendation. Through conducting comparison experiments on Tianpeng web dataset, the effectiveness and applicability of the proposed model are verified.

Qingxian Pan、Hongbin Dong、Yingjie Wang、Zhipeng Cai、Lizong Zhang

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College of Computer Science and Technology, Harbin Engineering University

School of Computer and Control Engineering, Yantai University

Department of Computer Science, Georgia State University

School of Computer Science and Engineering, University of Electronic Science and Technology of China

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2019

10.1155/2019/2121850

Wireless communications & mobile computing

Wireless communications & mobile computing

ISTP
ISSN：1530-8669
年,卷(期)：2019.2019
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