敖翔

中国科学院计算技术研究所

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  • 敖翔
  • 副研究员
简历:

2018年9月 — 今:中国科学院计算技术研究所,副研究员 2015年7月 — 2018年9月:中国科学院计算技术研究所,助理研究员 2010年9月 — 2015年7月:中国科学院计算技术研究所,博士生 2006年9月 — 2010年7月:浙江大学,计算机科学与技术,本科生

其他个人主页链接:http://mldm.ict.ac.cn/MLDM/~aox/

研究方向:

面向金融有关应用的文本、行为数据挖掘

社会任职:
获奖及荣誉:

2019 中国科学院青年创新促进会会员

2018/2017 计算所优秀研究人员

2018 北京洪堡论坛青年学术之星

2017 中国科学院计算所学术百星

代表论著:
期刊文章:[1] Xiang Ao, Ping Luo, Jin Wang, Fuzhen Zhuang, Qing He. Mining Precise-positioning Episode Rules from Event Sequences. IEEE Transactions on Data Engineering (IEEE TKDE), 30(3): 530-543, 2018. (CCF A类期刊,SCI)[2] Xiang Ao, Haoran Shi, Jin Wang, Luo Zuo, Hongwei Li, Qing He. Large-scale Frequent Episode Mining from Complex Event Sequences with Hierarchies. ACM Transactions on Intelligent Systems and Technology (ACM TIST), 10(4):36, 2019. (JCR二区,SCI)[3] Xiang Ao, Ping Luo, Chengkai Li, Fuzhen Zhuang, Qing He. Discovering and Learning Sensational Episodes of News Events. Information Systems (IS), 78 :68-80, 2018. (CCF B类期刊,SCI)[4] Xiang Ao, Ping Luo, Xudong Ma, Fuzhen Zhuang, Qing He, Zhongzhi Shi and Zhiyong Shen. Combining supervised and unsupervised models via unconstrained probabilistic embedding. Information Sciences (INS), 257: 101-114, 2014. (CCF B类期刊,SCI)[5] Thapana Boonchooa, Xiang Ao*, Yang Liu, Weizhong Zhao, Fuzhen Zhuang, Qing He. Grid-based DBSCAN : Indexing and Inference. Pattern Recognition (PR), 90: 271-284, 2019. (CCF B类期刊,SCI)会议文章:[1] Ling Luo, Xiang Ao*, Yan Song, Feiyang Pan, Min Yang and Qing He. Reading Like HER: Human Reading Inspired Extractive Summarization. To appear in the 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019. (CCF B)[2] Ling Luo, Xiang Ao*, Yan Song, Jinyao Li, Xiaopeng Yang, Qing He, Dong Yu. Unsupervised Neural Aspect Extraction with Sememes. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019. (CCF A)[3] Feiyang Pan, Shuokai Li, Xiang Ao, Pingzhong Tang, Qing He. Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2019. (CCF A)[4] Ling Luo, Xiang Ao*, Feiyang Pan, Tong Zhao, Ningzi Yu, Qing He. Beyond Polarity: Interpretable Financial Sentiment Analysis with Hierarchical Query-driven Attention. In International Joint Conference on Artificial Intelligence (IJCAI), 2018. (CCF A)[5] Xiang Ao, Yang Liu, Zhen Huang, Luo Zuo, Qing He. Free-rider Episode Screening via Dual Partition Model. In International Conference on Database Systems for Advanced Applications (DASFAA), 2018. (CCF B)[6] Jingwu Chen, Fuzhen Zhuang, Xin Hong, Xiang Ao, Xing Xie, Qing He. Attention-driven Factor Model for Explainable Personalized Recommendation. In International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2018. (CCF A)[7] Xiang Ao, Ping Luo, Jin Wang, Fuzhen Zhuang, Qing He. Mining Precise-positioning Episode Rules from Event Sequences. In IEEE International Conference on Data Engineering (ICDE, poster track), 2017. (CCF A)[8] Fuzhen Zhuang, Yingming Zhou, Fuzheng Zhang, Xiang Ao, Xing Xie, Qing He. Sequential Transfer Learning: Cross-domain Novelty Seeking Trait Mining for Recommendation. International World Wide Web Conference (WWW, poster track), Perth, Australia, 2017. (CCF A)[9] Xiang Ao, Ping Luo, Chengkai Li, Fuzhen Zhuang, Qing He. Online Frequent Episode Mining. IEEE International Conference on Data Engineering (ICDE), 2015. (CCF A)[10] Xiang Ao, Ping Luo, Chengkai Li, Fuzhen Zhuang, Qing He and Zhongzhi Shi. Discovering and learning sensational episodes of news events. International World Wide Web Conference (WWW, poster track), Seoul, Korea, April 2014. (CCF A)专利:[1] 描述性多维度事件序列的并行频繁情节挖掘方法与系统,2019年4月30日授权,专利号ZL201610524750.8。发明人:敖翔,左罗,罗平,庄福振,何清。[2] 一种并行的垂直交叉网络数据采集方法及系统,2016 年4 月13 日授权,专利号ZL201310146080.7。发明人:敖翔,何清,庄福振。[3] 一种面向大数据的分布式主题发现方法及系统,2017 年3 月29 日授权,专利号ZL201310526790.2。发明人:吴新宇,何清,庄福振,敖翔。[4] 一种大数据分类方法及系统,2017 年4 月12 日授权,专利号ZL201310727192.1。发明人:吴新宇,何清,庄福振,敖翔。
承担科研项目情况:

[1] NSFC基金面上项目:《保持高阶相似性的动态图表示学习方法及应用》,2020/01-2023.12,主持;

[2] NSFC青年基金项目:《序列大数据复杂情景模式发现算法研究》,2017/01-2019/12,主持;

[3] 中国科学院计算所创新项目子课题:《高通量区块链—区块链行为监管》,2018/05-2020/04,主持;

[4] 腾讯犀牛鸟社交广告专项:《基于深度学习的探索-利用(Explore-Exploit)算法研究》,2019/09-2020/08,主持

[5] 阿里巴巴AIR计划:《基于高阶多图融合嵌入的用户金融行为分析》,2019/08-2020/07,主持

[6] 蚂蚁金服安全专项科研基金:《人工智能欺诈识别聊天机器人》,2019/05-2020/04,主持;

[7] CCF-腾讯犀牛鸟科研基金:《基于深度强化学习的在线广告推荐》,2018/10-2019/10,主持;

[8] 德勤企业咨询(上海)有限公司联合研究:《债券舆情情感分析算法》,2017/08-2018/03,主持。

学科类别:
计算机软件与理论
所属部门:
中国科学院智能信息处理重点实验室
专家类别:
副高
杰青入选时间:
百人入选时间:
其他备注:
硕导计算机软件与理论
其他备注2:
其他备注3: