J
Jing Zhang
Researcher at Nanjing University of Science and Technology
Publications - 93
Citations - 1909
Jing Zhang is an academic researcher from Nanjing University of Science and Technology. The author has contributed to research in topics: Computer science & Crowdsourcing. The author has an hindex of 21, co-authored 80 publications receiving 1135 citations. Previous affiliations of Jing Zhang include Hefei University of Technology.
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Journal ArticleDOI
Learning from crowdsourced labeled data: a survey
TL;DR: This survey introduces the basic concepts of the qualities of labels and learning models, and introduces open accessible real-world data sets collected from crowdsourcing systems and open source libraries and tools.
Journal ArticleDOI
A novel data-driven stock price trend prediction system
TL;DR: Evaluations on the seven-year Shenzhen Growth Enterprise Market (China) transaction data show that the proposed stock price trend prediction system can make effective predictions, is robust to the market volatility, and outperforms some existing methods in terms of accuracy and return per trade.
Journal ArticleDOI
Active Learning With Imbalanced Multiple Noisy Labeling
TL;DR: A novel active learning framework with multiple imperfect annotators involved in crowdsourcing systems that solves the imbalanced multiple noisy labeling problem and three novel instance selection strategies are proposed to adapt PLAT for improving the learning performance.
Journal ArticleDOI
Multi-Class Ground Truth Inference in Crowdsourcing with Clustering
TL;DR: A novel algorithm, Ground Truth Inference using Clustering (GTIC), to improve the quality of integrated labels for multi-class labeling and is significantly superior to the others in terms of both accuracy and M-AUC.
Proceedings ArticleDOI
A Distributed Cache for Hadoop Distributed File System in Real-Time Cloud Services
TL;DR: Experimental results show that the novel cache system built on the top of the Hadoop Distributed File System can store files with a wide range in their sizes and has the access performance in a millisecond level in highly concurrent environments.