EntityManager: Managing Dirty Data Based on Entity Resolution

Abstract

Data quality is important in many data-driven applications, such as decision making, data analysis, and data mining. Recent studies focus on data cleaning techniques by deleting or repairing the dirty data, which may cause information loss and bring new inconsistencies. To avoid these problems, we propose EntityManager, a general system to manage dirty data without data cleaning. This system takes real-world entity as the basic storage unit and retrieves query results according to the quality requirement of users. The system is able to handle all kinds of inconsistencies recognized by entity resolution. We elaborate the EntityManager system, covering its architecture, data model, and query processing techniques. To process queries efficiently, our system adopts novel indices, similarity operator and query optimization techniques. Finally, we verify the efficiency and effectiveness of this system and present future research challenges.