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Probabilistic Ranking of Database Query Results

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44283

Das,  Gautam
Algorithms and Complexity, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45720

Weikum,  Gerhard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Zitation

Chaudhuri, S., Das, G., Hristidis, V., & Weikum, G. (2004). Probabilistic Ranking of Database Query Results. In Proceedings 2004 VLDB Conference: The 30th International Conference on Very Large Databases (VLDB) (pp. 888-899). St. Louis, USA: Morgan Kaufmann.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-29DB-9
Zusammenfassung
We investigate the problem of ranking answers to a database query when many tuples are returned. We adapt and apply principles of probabilistic models from Information Retrieval structured data. Our proposed solution is domain independent. It leverages data and workload statistics and corelations. Our ranking functions can be further customized for different applications. We present results of preliminary experiments which demonstrate the efficiency as well as the quality of our ranking system.