The stable marriage problem: structure and algorithms
The stable marriage problem: structure and algorithms
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Closest pair queries in spatial databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
The onion technique: indexing for linear optimization queries
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Introduction to Algorithms
On the 'Dimensionality Curse' and the 'Self-Similarity Blessing'
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the 17th International Conference on Data Engineering
Efficient Progressive Skyline Computation
Proceedings of the 27th International Conference on Very Large Data Bases
Optimal aggregation algorithms for middleware
Journal of Computer and System Sciences - Special issu on PODS 2001
Progressive skyline computation in database systems
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
Maximal vector computation in large data sets
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Continuous monitoring of top-k queries over sliding windows
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
ACM Transactions on Algorithms (TALG)
Branch-and-bound processing of ranked queries
Information Systems
Shooting stars in the sky: an online algorithm for skyline queries
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Capacity constrained assignment in spatial databases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Efficient sort-based skyline evaluation
ACM Transactions on Database Systems (TODS)
Efficient skyline querying with variable user preferences on nominal attributes
Proceedings of the VLDB Endowment
Computation and Monitoring of Exclusive Closest Pairs
IEEE Transactions on Knowledge and Data Engineering
Skyline-based Peer-to-Peer Top-k Query Processing
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Efficient Evaluation of Multiple Preference Queries
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Schedulability analysis for non-preemptive fixed-priority multiprocessor scheduling
Journal of Systems Architecture: the EUROMICRO Journal
Pareto optimality in house allocation problems
ISAAC'05 Proceedings of the 16th international conference on Algorithms and Computation
Matching query processing in high-dimensional space
Proceedings of the 20th ACM international conference on Information and knowledge management
Shortlisting top-K assignments
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
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Consider an internship assignment system, where at the end of each academic year, interested university students search and apply for available positions, based on their preferences (e.g., nature of the job, salary, office location, etc). In a variety of facility, task or position assignment contexts, users have personal preferences expressed by different weights on the attributes of the searched objects. Although individual preference queries can be evaluated by selecting the object in the database with the highest aggregate score, in the case of multiple simultaneous requests, a single object cannot be assigned to more than one users. The challenge is to compute a fair 1--1 matching between the queries and the objects. We model this as a stable-marriage problem and propose an efficient method for its processing. Our algorithm iteratively finds stable query-object pairs and removes them from the problem. At its core lies a novel skyline maintenance technique, which we prove to be I/O optimal. We conduct an extensive experimental evaluation using real and synthetic data, which demonstrates that our approach outperforms adaptations of previous methods by several orders of magnitude.