| 國際期刊論文: [1] Peipei Li#, Lu He, Haiyan Wang, Xuegang Hu, Yuhong Zhang*, Lei Li, and Xindong Wu, Learning from Short Text Streams with Topic Drifts, IEEE Transactions on Cybernetics, 48(9): 2697-2711, Sept. 2018. [2] Peipei Li#*, Haixun Wang, Hongsong Li, and Xindong Wu, Employing Semantic Context for Sparse Information Extraction Assessment, ACM Transactions on Knowledge Discovery from Data,12(5): 54:1-36, July 2018.
[3]Peng Zhou, Xuegang Hu,Peipei Li*, and Xindong Wu.Online Feature Selection for Class Imbalance Data.Knowledge-based Systems,136: 187-199,2017. [4]Yuhong Zhang, Guang Chu,Peipei Li*, Xuegang Hu,andXindong Wu.Three-layer Concept Drifting Detection in Text Data Streams. Neurocomputing, 260: 393-403, 2017. [5]Peipei Li*, HaixunWang, Kenny Q. Zhu,Zhongyuan Wang, Xuegang Hu, and Xindong Wu. A Large Probabilistic Semantic Network based Approach to Compute Term Similarity. IEEE Transactions on Knowledge and Data Engineering, 27(10): 2604-2617, 2015. [6]Peipei Li, Xindong Wu, Xuegang Hu, and Hao Wang*. An Incremental Decision Tree for Mining Multi-label Data. Applied Artificial Intelligence,29(10):992-1014, 2015. [7]Peipei Li*, Xindong Wu, Xuegang Hu, and Hao Wang. Learning Concept-Drifting Data Streams with Random Ensemble Decision Trees. NeuroComputing, 166(6): 68-83, 2015. [8]Xindong Wu,Peipei Li*and Xuegang Hu.Learning from Concept Drifting Data Streams with Unlabeled Data. NeuroComputing, 92(1): 145-155, 2012. [9]Peipei Li*, Xindong Wu and Xuegang Hu. Mining Recurring Concept Drifts with Limited Labeled Streaming Data. ACM Transactions on Intelligent Systemsand Technology, 3(2): 29:1-32,2012. [10]Peipei Li*, Xindong Wu, Xuegang Hu,Qianhui Liang and Yunjun Gao. A Random Decision Tree Ensemble for Mining Concept Drifts from Noisy Data Streams. Applied Artificial Intelligence, 24(7): 680-710, 2010. [11]Xuegang Hu,Peipei Li*, Xindong Wu, Gongqing Wu. A Semi-Random Multiple Decision-Tree Algorithm for Mining Data Streams. J. Comput. Sci. Technol. 22(5): 711-724, 2007. 會議論文: [12]Peipei Li*, Lu He,Junfeng Liu, Xuegang Hu and Xindong Wu. Max-Relevance and Min-Redundancy based Multi-label Data StreamClassification with Concept Drifting Detection.Submitted to AAA’17,2017. [13]Peipei Li*, Lu He, Xuegang Hu, Yuhong Zhang, Lei Li, and Xindong Wu. Concept based Short Text Stream Classification with Topic Drifting Detection. In: Proceedings ofInternational Conference on Data Mining (ICDM'16),pp. 1009-1014,2016. (EI檢索號:20171003423991) [14] Xugang Hu, Junhong He,Peipei Li*, Xindong Wu. Drifting Detection and Model Selection based Ensemble Classification for Data Streams with Unlabeled Data. In: Proceedings ofArtificial Intelligence Science and Technology (AIST’16),pp: 83- 90, 2017. [15]Peipei Li*, Hunxun Wang, Hongsong Li, and Xindong Wu. Assessing Sparse Information Extraction using Semantic Contexts. In:Proceedings of 22nd ACM International Conference on Information and Knowledge Management(CIKM’13), pp.1709-1714, 2013. [16]Peipei Li*, Hunxun Wang, Kenny Q. Zhu, Zhongyuan Wang, and Xindong Wu. Computing Term Similarity by Large Probabilistic isA Knowledge. In:Proceedings of CIKM’13,pp. 1401-1410, 2013. [17]Peipei Li*, Xindong Wu, Qianhui Liang, Xuegang Hu, Yuhong Zhang. Random Ensemble Decision Trees for Concept Drifting Data Streams. In:Proceedings of PAKDD’11, May 24-27, pp. 313-325, Shenzhen China, 2011. [18]Peipei Li*, Xindong Wu and Xuegang Hu. Learning from Concept Drifting Data Streams with Unlabeled Data. In:Proceedings of AAAI10-SA10, July 11-15, pp. 1945-1946, Atlanta, GA, United States, 2010. [19]Peipei Li*, Xindong Wu, and Xuegang Hu. Mining Recurring Concept Drifts with Limited Labeled Streaming Data. In:Proceeding of 2nd Asian Conference Machine Learning, Nov. 8-10, pp. 251-262, Tokyo, 2010. [20]Peipei Li*, Xuegang Hu, Q.-H. Liang, and Y.-J. Gao.Concept Drifting Detection on Noisy Streaming Data in Random Ensemble Decision Trees. In:Proceedings of the 6th International Conference on Machine Learning and Data Mining, pp. 236-250, 2009. [21]Peipei Li*, Qianhui Liang, Xindong Wu, and Xuegang Hu. Parameter Estimation in Semi-Random Decision Tree Ensembling on Streaming Data. In:Proceedings of PAKDD’09,pp. 376-388, 2009. [22]Qianhui Liang,Peipei Li*, P. C.K. Hung, and Xindong Wu. Clustering Web Services for Automatic Categorization. In:Proceedings of International Conference on Services Computing, pp. 380-387, 2009. [23]Peipei Li*, Xuegang Hu, and Xindong Wu. Mining Concept-drifting Data Streams with Multiple Semi-random Decision Trees. In:Proceedings of 4th International Conference on Advanced Data Mining and Applications, pp. 733-740, 2008. 國內期刊: [24] 胡學鋼#,王海平,郭丹,李培培*.圖算法求解帶有限長空位和one-off約束的模式匹配問題.模式識別與人工智能, 29(5):400-409,2016. 軟著: 胡學鋼、李培培、吳信東等. 數據流分類算法實驗工具包軟件 ETDSV1.0(登記號為2010SR062895) 專著: 胡學鋼、李培培、張玉紅、吳信東.數據流分類,清華大學出版社, 603千字, ISBN 978-7-302-40599-3, 2016.01.01. 專利: [1]李培培, 李磊, 張玉紅, 胡學鋼, 劉俊峰, 何路, 吳共慶, 吳信東.一種基于類與特征分布的多標簽數據流中概念漂移檢測方法. 申請號:201710151295.6, 申請日: 2017年03月14日(實際審查) [2]胡學鋼, 王博巖, 李培培. 自適應多標簽預測方法. 國家發明專利,專利號:ZL201510501816.7,專利申請日:2015年08月14日,授權公告日:2018年05月18日.
[3]胡學鋼,王海燕,李培培. 一種基于短文本擴展和概念漂移檢測的短文本數據 流分類方法,專利申請號201710994366.9,專利申請日:2017年10月23日. |