Generalized best-first search strategies and the optimality of A*
Journal of the ACM (JACM)
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Optimal aggregation algorithms for middleware
Journal of Computer and System Sciences - Special issu on PODS 2001
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Finding and approximating top-k answers in keyword proximity search
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Tree-depth, subgraph coloring and homomorphism bounds
European Journal of Combinatorics
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
IO-Top-k: index-access optimized top-k query processing
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Estimating Software Costs
Data stream query processing: a tutorial
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Efficient query evaluation on probabilistic databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Matching twigs in probabilistic XML
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Best position algorithms for top-k queries
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
A survey of top-k query processing techniques in relational database systems
ACM Computing Surveys (CSUR)
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
Type inference and type checking for queries on execution traces
Proceedings of the VLDB Endowment
Recursive Markov chains, stochastic grammars, and monotone systems of nonlinear equations
Journal of the ACM (JACM)
TOP-K projection queries for probabilistic business processes
Proceedings of the 12th International Conference on Database Theory
Evaluating TOP-K Queries over Business Processes
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Learning probabilistic relational models
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Dynamic probabilistic relational models
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Goal-oriented web-site navigation for on-line shoppers
Proceedings of the VLDB Endowment
Querying parse trees of stochastic context-free grammars
Proceedings of the 13th International Conference on Database Theory
Probabilistic XML via Markov Chains
Proceedings of the VLDB Endowment
Optimal top-k query evaluation for weighted business processes
Proceedings of the VLDB Endowment
Querying and updating probabilistic information in XML
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Algorithmic verification of recursive probabilistic state machines
TACAS'05 Proceedings of the 11th international conference on Tools and Algorithms for the Construction and Analysis of Systems
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The core logic of web applications that suggest some particular service, such as online shopping, e-commerce etc., is typically captured by Business Processes (BPs). Among all the (maybe infinitely many) possible execution flows of a BP, analysts are often interested in identifying flows that are "most important", according to some weight metric. The goal of the present paper is to provide efficient algorithms for top-k query evaluation over the possible executions of Business Processes, under some given weight function. Unique difficulties in top-k analysis in this settings stem from (1) the fact that the number of possible execution flows of a given BP is typically very large, or even infinite in presence of recursion and (2) that the weights (e.g., likelihood, monetary cost, etc.) induced by actions performed during the execution (e.g., product purchase) may be inter-dependent (due to probabilistic dependencies, combined discount deals etc.). We exemplify these difficulties, and overcome them to provide efficient algorithms for query evaluation where possible. We also describe in details an application prototype that we have developed for recommending optimal navigation in an online shopping web site that is based on our model and algorithms.