Distance measures for signal processing and pattern recognition
Signal Processing
Elements of information theory
Elements of information theory
Combining fuzzy information from multiple systems (extended abstract)
PODS '96 Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Preference structures and their numerical representations
Theoretical Computer Science
Optimal aggregation algorithms for middleware
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Supporting Ranked Boolean Similarity Queries in MARS
IEEE Transactions on Knowledge and Data Engineering
Processing Complex Similarity Queries with Distance-Based Access Methods
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Querying with Intrinsic Preferences
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Proceedings of the 17th International Conference on Data Engineering
FeedbackBypass: A New Approach to Interactive Similarity Query Processing
Proceedings of the 27th International Conference on Very Large Data Bases
Fast Evaluation Techniques for Complex Similarity Queries
Proceedings of the 27th International Conference on Very Large Data Bases
A Sound Algorithm for Region-Based Image Retrieval Using an Index
DEXA '00 Proceedings of the 11th International Workshop on Database and Expert Systems Applications
Query Reformulation for Content Based Multimedia Retrieval in MARS
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Efficient similarity search and classification via rank aggregation
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Evaluating Top-k Queries over Web-Accessible Databases
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Foundations of preferences in database systems
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Multi-objective query processing for database systems
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
SaLSa: computing the skyline without scanning the whole sky
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Designing personalized curricula based on student preferences
SIGDOC '07 Proceedings of the 25th annual ACM international conference on Design of communication
Efficient sort-based skyline evaluation
ACM Transactions on Database Systems (TODS)
Data & Knowledge Engineering
Processing preference queries in standard database systems
ADVIS'06 Proceedings of the 4th international conference on Advances in Information Systems
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Complex multimedia queries, aiming to retrieve from large databases those objects that best match the query specification, are usually processed by splitting them into a set of m simpler sub-queries, each dealing with only some of the query features. To determine which are the overall best-matching objects, a rule is then needed to integrate the results of such sub-queries, i.e., how to globally rank the m-dimensional vectors of matching degrees, or partial scores, that objects obtain on the m sub-queries. It is a fact that state-of-the-art approaches all adopt as integration rule a scoring function, such as weighted average, that aggregates the m partial scores into an overall (numerical) similarity score, so that objects can be linearly ordered and only the highest scored ones returned to the user. This choice however forces the system to compromise between the different sub-queries and can easily lead to miss relevant results. In this paper we explore the potentialities of a more general approach, based on the use of qualitative preferences, able to define arbitrary partial (rather than only linear) orders on database objects, so that a larger flexibility is gained in shaping what the user is looking for. For the purpose of efficient evaluation, we propose two integration algorithms able to work with any (monotone) partial order (thus also with scoring functions): MPO, which delivers objects one layer of the partial order at a time, and iMPO, which can incrementally return one object at a time, thus also suitable for processing top k queries. Our analysis demonstrates that using qualitative preferences pays off. In particular, using Skyline and Region-prioritized Skyline preferences for queries on a real image database, we show that the results we get have a precision comparable to that obtainable using scoring functions, yet they are obtained much faster, saving up to about 70% database accesses.