Flexible querying of lifelong learner metadata

Abstract

We propose combining query approximation and query relaxation techniques in order to support flexible querying of heterogeneous data arising from lifelong learners' educational and work experiences. A key aim of such querying facilities is to allow learners to identify possible choices for their future learning and professional development from what others have done. With our approach, query results can be computed incrementally, in polynomial time, and returned in order of increasing "distance" from the user's original query