计算机科学与技术学院

代表性SCI期刊论文（第一作者SCI论文10篇，其中CCF A类4篇，中科院大类1区2篇）

[1] Jing Zhang, Min Wu, & Victor S. Sheng. (Online). Ensemble Learning from Crowds. IEEE Transactions on Knowledge and Data Engineering, DOI: 10.1109/TKDE.2018.2860992. (CCF A类,中科院大类2区)

[2]Jing Zhang, Victor S. Sheng, Tao Li, & Xindong Wu. (May 2018). Improving Crowdsourced Label Quality Using Noise Correction.IEEE Transactions on Neural Networks and Learning Systems,vol. 29, no. 5, pp. 1675–1688. (中科院大类1区, CCF B类)

[3]Jing Zhang, Shicheng Cui, Yan Xu, Qianmu Li, & Tao Li. (May 2018). A Novel Data-Driven Stock Price Trend Prediction System.Expert Systems with Applications, vol. 97, pp. 60–69. (中科院大类2区, CCF C类)

[4]Jing Zhang, Victor S. Sheng, Qianmu Li, Jian Wu, & Xindong Wu. (Mar. 2017). Consensus Algorithms for Biased Labeling in Crowdsourcing.Information Sciences, vol. 382, pp. 254–273. (中科院大类2区, CCF B类)

[5]Jing Zhang, Xindong Wu, & Victor S. Sheng. (Dec. 2016). Learning from Crowdsourced Labeled Data: a Survey.Artificial Intelligence Review, vol. 46, no. 4, pp. 543–576. (中科院大类3区)

[6]Jing Zhang, Qianmu Li, & Wei Zhou. (Sept. 2016). HDCache: A Distributed Cache System for Real-Time Cloud Services.Journal of Grid Computing. vol. 14, no. 3, pp. 407–428. (中科院大类3区, CCF C类)

[7]Jing Zhang, Victor S. Sheng, Jian Wu, & Xindong Wu. (Apr. 2016). Multi-Class Ground Truth Inference in Crowdsourcing with Clustering.IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 4, pp. 1080–1085. (CCF A类,中科院大类2区)

[8]Jing Zhang, Victor S. Sheng, Bryce A. Nicholson, & Xindong Wu. (Dec. 2015). CEKA: A Tool for Mining the Wisdom of Crowds.Journal of Machine Learning Research, vol. 16, pp. 2853–2858. (CCF A类, 中科院大类2区)

[9]Jing Zhang, Xindong Wu, & Victor S. Sheng. (May 2015). Active Learning with Imbalanced Multiple Noisy Labeling.IEEE Transactions on Cybernetics, vol. 45, no. 5, pp. 1081–1093. (中科院大类1区, CCF B类)

[10]Jing Zhang, Xindong Wu, & Victor S. Sheng. (Feb. 2015). Imbalanced Multiple Noisy Labeling.IEEE Transactions on Knowledge and Data Engineering, vol. 27, no. 2, pp. 489–503. (CCF A类，中科院大类2区)

代表性会议论文（第一作者论文6篇，其中CCF A类Research Track 2篇）

[11] Jing Zhang & Xindong Wu. (Aug. 19-23, 2018). Multi-Label Inference for Crowdsourcing. InProceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), London, United Kingdom. (CCF A类，Research Track)

[12]Jing Zhang, Victor S. Sheng, & Tao Li. (Aug. 7-11, 2017). Label Aggregation for Crowdsourcing with Bi-Layer Clustering. InProceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Tokyo, Japan, pp. 921–924. (CCF A类，Research Track)

[13]Jing Zhang, Victor S. Sheng, Jian Wu, Xiaoqin Fu, & Xindong Wu. (Oct. 19-23, 2015). Improving Label Quality in Crowdsourcing Using Noise Correction. InProceedings of the 24th ACM International Conference on Information and Knowledge Management (CIKM), Melbourne, Australia, pp. 1931–1934. (CCF B类会议)

[14]Jing Zhang, Xindong Wu, & Victor S. Sheng. (Aug. 25-28, 2013). A Threshold Method for Imbalanced Multiple Noisy Labeling. InProceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Niagara Falls, Canada, pp. 61–65.

[15]Jing Zhang, Xindong Wu, & Victor S. Sheng. (Jul. 14-18, 2013). Imbalanced Multiple Noisy Labeling for Supervised Learning. InProceedings of the 27th AAAI Conference on Artificial Intelligence (AAAI), Bellevue, Washington, USA, pp. 1651–1652. (CCF A类, Poster)

[16]Jing Zhang, Gongqing Wu, Xuegang Hu. & Xindong Wu. (Sept. 20-23, 2012). A Distributed Cache for Hadoop Distributed File System in Real-Time Cloud Services. InProceedings of the 13th ACM/IEEE International Conference on Grid Computing (GRID), Beijing, China, pp.12–21.