On the range maximum-sum segment query problem

On the range maximum-sum segment query problem (2004)

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by Kuan-yu Chen , Kun-mao Chao

Venue:	Proceedings of the 15th International Symposium on Algorithms And Computation, LNCS 3341
Citations:	11 - 3 self

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Datum	Value	Source
TITLE	On the range maximum-sum segment query problem	INFERENCE
AUTHOR NAME	Kuan-yu Chen	SVM HeaderParse 0.2
AUTHOR AFFIL	1 Department of Computer Science and Information Engineering; 2 Graduate Institute of Biomedical Electronics and Bioinformatics; 3 Graduate Institute of Networking and Multimedia	SVM HeaderParse 0.2
AUTHOR ADDR	National Taiwan University, Taipei, Taiwan 106	SVM HeaderParse 0.2
AUTHOR NAME	Kun-mao Chao	SVM HeaderParse 0.2
AUTHOR AFFIL	1 Department of Computer Science and Information Engineering; 2 Graduate Institute of Biomedical Electronics and Bioinformatics; 3 Graduate Institute of Networking and Multimedia	SVM HeaderParse 0.2
AUTHOR ADDR	National Taiwan University, Taipei, Taiwan 106	SVM HeaderParse 0.2
ABSTRACT	The range minimum query problem, RMQ for short, is to preprocess a sequence of real numbers A[1...n] for subsequent queries of the form: “Given indices i, j, what is the index of the minimum value of A[i...j]? ” This problem has been shown to be linearly equivalent to the LCA problem in which a tree is preprocessed for answering the lowest common ancestor of two nodes. It has also been shown that both the RMQ and LCA problems can be solved in linear preprocessing time and constant query time under the unit-cost RAM model. This paper studies a new query problem arising from the analysis of biological sequences. Specifically, we wish to answer queries of the form: “Given indices i and j, what is the maximum-sum segment of A[i...j]? ” We establish the linear equivalence relation between RMQ and this new problem. As a consequence, we can solve the new query problem in linear preprocessing time and constant query time under the unit-cost RAM model. We then present alternative linear time solutions for two other biological sequence analysis problems to demonstrate the utilities of the techniques developed in this paper.	SVM HeaderParse 0.2
YEAR	2004	INFERENCE
VENUE	Proceedings of the 15th International Symposium on Algorithms And Computation, LNCS 3341	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	294--305	INFERENCE
VOLUME	3341	INFERENCE
CITATIONS	18 found	ParsCit 1.0