Probabilistic data cleaning.

The goal of this project is to study and develop probabilistic data cleaning techniques. Data cleaning refers to the process of detecting and repairing errors, duplicates and anomalies in data. In response to the large amounts of "dirty" data in today's digital society, the data quality problem is enjoying a lot of interest from various disciplines in computer science.

Keywords:ARTIFICIAL INTELLIGENCE, COMPUTER SCIENCE, DATABASE SYSTEMS

Disciplines:Applied mathematics in specific fields, Artificial intelligence, Computer architecture and networks, Distributed computing, Information sciences, Information systems, Programming languages, Scientific computing, Theoretical computer science, Visual computing, Other information and computing sciences, Cognitive science and intelligent systems

Project type:Collaboration project