Probabilistic information retrieval approach for ranking of database query 
results

Chaudhuri, Surajit; Das, Gautam; Hristidis, Vagelis; Weikum, Gerhard

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

Probabilistic information retrieval approach for ranking of database query results

MPS-Authors

/persons/resource/persons44283

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

/persons/resource/persons45720

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

External Resource

No external resources are shared

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

Chaudhuri, S., Das, G., Hristidis, V., & Weikum, G. (2006). Probabilistic information retrieval approach for ranking of database query results. ACM Transactions on Database Systems, 31, 1134-1168.

Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-23BF-A

Abstract

We investigate the problem of ranking the answers to a database query when many tuples are returned. In particular, we present methodologies to tackle the problem for conjunctive and range queries, by adapting and applying principles of probabilistic models from information retrieval for structured data. Our solution is domain independent and leverages data and workload statistics and correlations. We evaluate the quality of our approach with a user survey on a real database. Furthermore, we present and experimentally evaluate algorithms to efficiently retrieve the top ranked results, which demonstrate the feasibility of our ranking system.