Overview
Topic status: We're looking for students to study this topic.
Currently there are two main research directions in data mining. One direction is concerned with the design of efficient algorithms for discovering knowledge, and another is concerned with the interpretations of the discovered knowledge. Most research in data mining has so far focused on the former direction and various techniques have been developed for efficiently mining frequent patterns and association rules, but little achievement has been made on interpreting the discovered knowledge due to two obstacles: the overwhelmingly large volume of discovered patterns (or rules) and the lack of semantic information along with the discovered knowledge.
The goal of this research is to develop techniques to annotate the discovered patterns and associations with semantically enriched descriptions and context information. This semantic information can suggest the potential meaning of the patterns or rules and to help users decide whether and how to explore and use the discovered knowledge.
Good Java, C# and Database skills are required
- Study level
- Honours
- Supervisors
- QUT
- Organisational unit
Science and Engineering Faculty
- Research area
- Contact
- Please contact the supervisor.
Associate Professor Yue Xu
