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University of Illinois at Urbana-Champaign
Enabling Data Retrieval: By Ranking and Beyond
Abstract
dc:descriptionThis 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.
Degree
thesis:*- Name thesis:degree_name
- Ph.D.
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Computer Science
- Grantor
- University of Illinois at Urbana-Champaign
- Year dc:date
- 2015
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Li, Chengkai
- Contributors dc:contributor
-
- Chang, Kevin Chen-Chuan
Subjects
dc:subject × 1Rights
- Language dc:language
- eng
Identifiers
dc:identifier.*- Identifier
- (MiAaPQ)AAI3290293
- OAI identifier oai:identifier
- oai:www.ideals.illinois.edu:2142/81783