Handling metadata in scope of coreference detection in data collections

01 January 2013 → 31 December 2016
Regional and community funding: Special Research Fund
Research disciplines
  • Natural sciences
    • Applied mathematics in specific fields
    • Computer architecture and networks
    • Distributed computing
    • Information sciences
    • Information systems
    • Programming languages
    • Scientific computing
    • Theoretical computer science
    • Visual computing
    • Other information and computing sciences
databases coreference knowledge extraction metadata
Project description

Database systems allow to model information in a well-structured manner. Unfortunately, many databases cope with quality problems. A significant problem is the existence of coreferent data, which means that the same real world entity is described multiple times within one database. Due to errors, inaccuracies and a lack of standardization, coreferent data are not bound to be equal, which makes the finding of coreferent data a challenging topic. In this project it is studied how metadata can help to extract semantic knowledge which can be used to improve the detection of coreferent database objects.