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The ICDM19 PhD Forum will be held on Nov. 8, 2019. This workshop will highlight work of PhD and PhD-bound Masters students, which will become the core of their thesis. It spans various topics of data mining and related fields such as machine learning, artificial intelligence, statistics, databases, information retrieval, social media analysis, and multimedia and web mining.

During the workshop, invited students will give the presentations of their on going works, while researchers with experience in supervising and examining doctoral students will participate and provide feedback on these presentations. This year we will also have a keynote session with two speakers where the well-known, successful Prof. Bing Liu, and Dr. Neil Shah will discuss topics that are relevant to PhDs or PhD-bound students,e.g., discuss various tips of academic and industry, how to work with supervisors to in a win-win way, how to reach the career goals. Any kinds of questions can be raised to discuss over face to face in this session. In addition, we will organize a panel session "AI in data mining" to discuss how AI is related to data mining and some potential topics, and demonstrate some examples from panel speakers.

The workshop is open to anyone who is interested in !

Co-chairs : Ivan Brugere , Salesforce    &    Yi Yu, National Institute of Informatics


  • Student Presentations 1 (01:35pm-3:20pm), Room 407---Session chair (Fiete Lüer, Carl Yang)
    • Enhancing Clinical Name Entity Recognition Based on Hybrid Deep Learning Scheme
      Robert Phan, Thoai Man Luu, and Girija Chetty
    • Action-Triggering Recommenders: Uplift Optimization and Persuasive Explanation
      Masahiro Sato, Shin Kawai, and Hajime Nobuhara
    • Who is Who: Name Disambiguation in Large-Scale Scientific Literature
      Hongliang Du, Zhiyi Jiang, and Jianliang Gao
    • On Fairness-aware Learning for Non-discriminative Decision-making
      Wenbin Zhang, Xuejiao Tang, and Jianwu Wang
    • Anomaly Detection in Time Series using Generative Adversarial Networks
      Fiete Lüer, Dominik Mautz, and Christian Böhm
    • cube2net: Efficient Query-Specific Network Construction with Data Cube Organization
      Carl Yang, Mengxiong Liu, Shibi He, Jian Peng, and Jiawei Han
    • Characterizing Voters Preferences in Political Elections Using Random Utility Theory: A Case of Study
      Constanza Contreras-Piña, Charles Thraves, and Sebastian Rios
  • Student Presentations 2 (04:40pm - 05:48pm), Room 407---Session chair (Donghuo Zeng, Kunal Rajput)
    • Loyal Consumers or One-time Deal Hunters: Repeat Buyer Prediction for E-commerce
      Bo Zhao, Atsuhiro Takasu, Ramin Yahyapour, and Xiaoming Fu
    • Field-aware Knowledge Tracing Machine by Modelling Students’ Dynamic Learning Procedure and Item Difficulty
      Wenbin Gan, Yuan Sun, Shiwei Ye, Ye Fan, and Yi Sun
    • Learning Joint Embedding for Cross-Modal Retrieval
      Donghuo Zeng, Keizo Oyama
    • Risk Factors Identification for Heart Disease in unstructured dataset using Deep Learning Approach
      Kunal Rajput, Girija Chetty, and Rachel Davey
    • Planting Synchronisation Trees for Discovering Interaction Patterns among Brain Regions
      Lena G. M. Bauer, Philipp Grohs, Afra Wohlschläger, and Claudia Plant


Bing Liu

Ivan Brugere

Neil Shah

Rajiv R. Shah

Yi Yu

Bing Liu Ivan Brugere Neil Shah Rajiv R. Shah Yi Yu