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Enabling Data Retrieval: By Ranking and Beyond
Doctoral Committee Chair(s)
Chang, Kevin Chen-Chuan
Department of Study
Degree Granting Institution
University of Illinois at Urbana-Champaign
This thesis further studies how to enable retrieval mechanisms beyond just ranking. Our explorative study in this direction is exemplified by two novel proposals---One is to integrate clustering and ranking of database query results; the other is to support inverse ranking queries that provide ranks of objects in query context. Injecting such non-traditional facilities into databases presents non-trivial challenges in both defining query semantics and designing query processing methods. We extended SQL language to express such queries and invented partition- and summary-driven approaches to process them.