Embedding learning in recommendations and code analysis
|Title:||Embedding learning in recommendations and code analysis|
|Date:||April 12, 2019 (Friday)|
|Time:||11:00 am - 12:00 pm|
|Venue:||Room 121, 1/F, Ho Sin-Hang Engineering Building, The Chinese University of Hong Kong, Shatin, N.T.|
|Speaker:|| Prof. Xu Guandong
University of Technology Sydney
Embedding learning is a widely used machine learning algorithm and has been successfully applied in various data sources, e.g. matrices, sequences, and graphs, and various application tasks, e.g. NLP, code analysis, and recommendations. The major advantage of embedding learning is to derive concise but representative semantics from original data observations. In this talk, we will introduce our recent research work on knowledge graph embedding for recommendations, and source code embedding for code summarization.
Dr. Guandong Xu is a Professor at University of Technology Sydney and CUHK visiting Professor, specialising in Data Science, Data Analytics, Recommender Systems, Web Mining, Text mining and NLP, Social Network Analysis, and Social Media Mining. He has published three monographs, dozens of book chapters and edited conference proceedings, and 200+ journal and conference papers in decent journals and conferences. He leads Data Science and Machine Intelligence Lab at UTS. He is the assistant Editor-in-Chief of World Wide Web Journal and has been serving in editorial board or as guest editors for several international journals. He has received a number of Awards from academia and industry community, such as 2018 Top-10 Australian Analytics Leader Award.
Enquiries: Mr. Cyrus Lee at tel. 3943 8440
For more information, please refer to http://www.cse.cuhk.edu.hk/en/events