Automatic text processing
Predicate migration: optimizing queries with expensive predicates
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Optimizing disjunctive queries with expensive predicates
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
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
A framework for expressing and combining preferences
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Minimal probing: supporting expensive predicates for top-k queries
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Top-k selection queries over relational databases: Mapping strategies and performance evaluation
ACM Transactions on Database Systems (TODS)
Introduction to Algorithms
Optimizing Multi-Feature Queries for Image Databases
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Supporting Incremental Join Queries on Ranked Inputs
Proceedings of the 27th International Conference on Very Large Data Bases
Using Fagin's Algorithm for Merging Ranked Results in Multimedia Middleware
COOPIS '99 Proceedings of the Fourth IECIS International Conference on Cooperative Information Systems
Query Processing Issues in Image(Multimedia) Databases
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Optimal aggregation algorithms for middleware
Journal of Computer and System Sciences - Special issu on PODS 2001
Evaluating Top-k Queries over Web-Accessible Databases
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Algorithms and applications for answering ranked queries using ranked views
The VLDB Journal — The International Journal on Very Large Data Bases
Evaluating top-k queries over web-accessible databases
ACM Transactions on Database Systems (TODS)
Efficient top-K query calculation in distributed networks
Proceedings of the twenty-third annual ACM symposium on Principles of distributed computing
Optimizing Access Cost for Top-k Queries over Web Sources: A Unified Cost-Based Approach
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
RankSQL: query algebra and optimization for relational top-k queries
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Top-k query evaluation with probabilistic guarantees
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
A survey of top-k query processing techniques in relational database systems
ACM Computing Surveys (CSUR)
Efficient network aware search in collaborative tagging sites
Proceedings of the VLDB Endowment
Processing top-N relational queries by learning
Journal of Intelligent Information Systems
TJJE: An efficient algorithm for top-k join on massive data
Information Sciences: an International Journal
Efficient execution of top-k SPARQL queries
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
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This paper addresses the problem of evaluating ranked top-k queries with expensive predicates. As major DBMSs now all support expensive user-defined predicates for Boolean queries, we believe such support for ranked queries will be even more important: First, ranked queries often need to model user-specific concepts of preference, relevance, or similarity, which call for dynamic user-defined functions. Second, middleware systems must incorporate external predicates for integrating autonomous sources typically accessible only by per-object queries. Third, ranked queries often accompany Boolean ranking conditions, which may turn predicates into expensive ones, as the index structure on the predicate built on the base table may be no longer effective in retrieving the filtered objects in order. Fourth, fuzzy joins are inherently expensive, as they are essentially user-defined operations that dynamically associate multiple relations. These predicates, being dynamically defined or externally accessed, cannot rely on index mechanisms to provide zero-time sorted output, and must instead require per-object probe to evaluate. To enable probe minimization, we develop the problem as cost-based optimization of searching over potential probe schedules. In particular, we decouple probe scheduling into object and predicate scheduling problems and develop an analytical object scheduling optimization and a dynamic predicate scheduling optimization, which combined together form a cost-effective probe schedule.