Optimal aggregation algorithms for middleware
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Database Management Systems
Minimal probing: supporting expensive predicates for top-k queries
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Towards Efficient Multi-Feature Queries in Heterogeneous Environments
ITCC '01 Proceedings of the International Conference on Information Technology: Coding and Computing
Algorithms and applications for answering ranked queries using ranked views
The VLDB Journal — The International Journal on Very Large Data Bases
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
RankSQL: query algebra and optimization for relational top-k queries
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
An efficient and versatile query engine for TopX search
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Boolean + ranking: querying a database by k-constrained optimization
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
IO-Top-k: index-access optimized top-k query processing
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Enabling soft queries for data retrieval
Information Systems
Progressive and selective merge: computing top-k with ad-hoc ranking functions
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
UPRE: User Preference Based Search System
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Supporting top-K join queries in relational databases
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Multi-objective query processing for database systems
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Best position algorithms for top-k queries
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
On Top-k Search with No Random Access Using Small Memory
ADBIS '08 Proceedings of the 12th East European conference on Advances in Databases and Information Systems
| Hi-index | 0.00 |
Methods of top-ksearch with no random access can be used to find kbest objects using sorted access to the sources of attribute values. In this paper we present new heuristics over the NRAalgorithm that can be used for fast search of top-kobjects using wide range of user preferences. NRAalgorithm usually needs a periodical scan of a large number of candidates during the computation. In this paper we propose methods of no random access top-ksearch that optimize the candidate list maintenance during the computation to speed up the search. The proposed methods are compared to a table scan method typically used in databases. We present results of experiments showing speed improvement depending on number of object attributes expressed in a user preferences or selectivity of user preferences.