Yaoshu Wang is a researcher in Shenzhen Institute of Computer Science. He worked as a research fellow in the Database Group at School of Computer Science and Engineering from the University of New South Wales, and received his Ph.D. from the same university, under the guidance of Prof. Wei Wang.
- Similarity Query Processing,
- Query Optimization
- Data cleaning
- Machine learning
- Jianbin Qin, Chuan Xiao, Yaoshu Wang, Wei Wang, Xuemin Lin, Yoshiharu Ishikawa, Guoren Wang：Generalizing the Pigeonhole Principle for Similarity Search in Hamming Space. IEEE Transactions on Knowledge and Data Engineering(TKDE)
- Yaoshu Wang, Chuan Xiao, Jianbin Qin, Xin Cao, Yifang Sun, Wei Wang, Makoto Onizuka：Monotonic Cardinality Estimation of Similarity Selection: A Deep Learning Approach. ACM Conference on Management of Data（SIGMOD 2020）, June 14-19, 2020, Portland Oregon, USA
RML (Logic Rules and Machine Learning) is a system that mainly builds a data availability cloud platform. Under the guidance of the self-developed data quality foundational theory, RML uses the combination of rules and AI under a unified logic framework to solve data consistency, timeliness, and the same problem of accuracy, completeness, and substance. The system is oriented to centralized/distributed data, relational/graph data to create a one-stop solution for data and knowledge collection, quality evaluation, data analysis, data error checking, entity recognition, data repair, and data fusion. RML takes advantage of China’s data scale to form a positive cycle of two-way interaction between data and the platform and accelerate the high-quality conversion of data to digital intelligence. It promotes the high-quality application of data production factors in various industries, consolidates the digital economy’s infrastructure, and leads the development of global data availability.