Optimizing queries over multimedia repositories
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Combining fuzzy information from multiple systems (extended abstract)
PODS '96 Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
An overview of query optimization in relational systems
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Optimal aggregation algorithms for middleware
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Modeling high-dimensional index structures using sampling
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Optimizing Multi-Feature Queries for Image Databases
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Accelerating High-Dimensional Nearest Neighbor Queries
SSDBM '02 Proceedings of the 14th International Conference on Scientific and Statistical Database Management
SSD '95 Proceedings of the 4th International Symposium on Advances in Spatial Databases
Query Processing Issues in Image(Multimedia) Databases
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
The Threshold Algorithm: From Middleware Systems to the Relational Engine
IEEE Transactions on Knowledge and Data Engineering
Efficient and generic evaluation of ranked queries
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Finding the plateau in an aggregated time series
WAIM '06 Proceedings of the 7th international conference on Advances in Web-Age Information Management
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Assume a database storing N objects with d numerical attributes or feature values. All objects in the database can be assigned an overall score that is derived from their single feature values (and the feature values of a user-defined query). The problem considered here is then to efficiently retrieve the k objects with minimum (or maximum) overall score. The well-known threshold algorithm (TA) was proposed as a solution to this problem. TA views the database as a set of d sorted lists storing the feature values. Even though TA is optimal with regard to the number of accesses, its overall access cost can be high since, in practice, some list accesses may be more expensive than others. We therefore propose to make TA access cost aware by choosing the next list to access such that the overall cost is minimized. Our experimental results show that this overall cost is close to the optimal cost and significantly lower than the cost of prior approaches.