Optimal aggregation algorithms for middleware
Journal of Computer and System Sciences - Special issu on PODS 2001
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Progressive and selective merge: computing top-k with ad-hoc ranking functions
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
A survey of top-k query processing techniques in relational database systems
ACM Computing Surveys (CSUR)
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Top-k combinatorial skyline queries
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part II
Skyline sets query and its extension to spatio-temporal databases
DNIS'10 Proceedings of the 6th international conference on Databases in Networked Information Systems
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Conventional search techniques are mainly designed to return a ranked list of single objects that are relevant to a given query. However, they do not meet the criteria for retrieving a combination of objects that is close to the query. This paper presents top-k query processing in which Euclidean distance is used as the scoring function for combinatorial objects. We also propose a pruning method based on clustering and efficiently select object combinations by pruning clusters that do not contain potential candidates for the top-k results. We compared the proposed method with the method that enumerates all the combinatorial objects and calculates the distance to the query. Experimental results revealed that the proposed method improves the processing efficiency to about 95% at maximum.