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Probabilistic Ranking of Database Query Results

Tham khảo tài liệu 'probabilistic ranking of database query results', công nghệ thông tin, cơ sở dữ liệu phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Probabilistic Ranking of Database Query Results Gautam Das Surajit Chaudhuri Microsoft Research One Microsoft Way Redmond WA 98o53 USA surajitc gautamd @microsoft.com Vagelis Hristidis School of Comp. Sci. Florida Intl. University Miami FL 33199 USA vagelis@cs.fiu.edu Gerhard Weikum MPI Informatik Stuhlsatzenhausweg 85 D-66123 SaarbrueCken Germany weikum @ mpi-sb.mpg.de Abstract 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 for structured data. Our proposed solution is domain independent. It leverages data and workload statistics and correlations. 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. 1. Introduction Database systems support a simple Boolean query retrieval model where a selection query on a SQL database returns all tuples that satisfy the conditions in the query. This often leads to the Many-Answers Problem when the query is not very selective too many tuples may be in the answer. We use the following running example throughout the paper Example Consider a realtor database consisting of a single table with attributes such as TID Price City Bedrooms Bathrooms LivingArea SchoolDistrict View Pool Garage BoatDock . . Each tuple represents a home for sale in the US. Consider a potential home buyer searching for homes in this database. A query with a not very selective Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage the VLDB copyright notice and the title of the publication and its date appear and notice is given that copying is by permission of the Very Large Data Base Endowment. To copy otherwise or to republish requires a fee and or special permission from the Endowment .