Partial Sorting Problem on Evolving Data

doi:10.1007/s00453-017-0295-3

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	Partial Sorting Problem on Evolving Data
	Huang, Qin 1,5; Liu, Xingwu 2,3,4; Sun, Xiaoming 4,5; Zhang, Jialin 4,5
刊名	ALGORITHMICA
	2017-11-01
卷号	79 期号:3 页码:960-983
ISSN号	0178-4617
DOI	10.1007/s00453-017-0295-3
英文摘要	In this paper we investigate the top-k-selection problem, i.e. to determine and sort the top k elements, in the dynamic data model. Here dynamic means that the underlying total order evolves over time, and that the order can only be probed by pair-wise comparisons. It is assumed that at each time step, only one pair of elements can be compared. This assumption of restricted access is reasonable in the dynamic model, especially for massive data sets where it is impossible to access all the data before the next change occurs. Previously only two special cases were studied (Anagnostopoulos et al. in 36th international colloquium on automata, languages and programming (ICALP). LNCS, vol 5566, pp 339-350, 2009) in this model: selecting the element of a given rank, and sorting all elements. This paper systematically deals with 1 <= k <= n. Specifically, we identify the critical point k* such that the top-k-selection problem can be solved error-free with probability 1 - 0(1) if and only if k = 0(k). A lower bound of the error when k = Omega(k) is also determined, which actually is tight under some conditions. In contrast, we show that the top-k-set problem, which means finding the top k elements without sorting them, can be solved error-free with probability 1 - o(1) for all 1 <= k <= n. Additionally, we consider some extensions of the dynamic data model and show that most of these results still hold.
资助项目	National Key Research and Development Program of China[2016YFB1000201] ; National Key Research and Development Program of China[2016YFB1000604] ; State Key Laboratory of Software Development Environment Open Fund[SKLSDE-2016KF-01] ; Science Foundation of Shenzhen City in China[JCYJ20160419152942010] ; National Natural Science Foundation of China[61222202] ; National Natural Science Foundation of China[61433014] ; National Natural Science Foundation of China[61502449] ; National Natural Science Foundation of China[61602440] ; China National Program for support of Top-notch Young Professionals
WOS研究方向	Computer Science ; Mathematics
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000410381100018
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/6681]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Liu, Xingwu
作者单位	1.Beihang Univ, State Key Lab Software Dev Environm, Beijing, Peoples R China 2.Beihang Univ Shenzhen, Res Inst, Shenzhen, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 4.Univ Chinese Acad Sci, Beijing, Peoples R China 5.Chinese Acad Sci, CAS Key Lab Network Data Sci & Technol, Inst Comp Technol, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Huang, Qin,Liu, Xingwu,Sun, Xiaoming,et al. Partial Sorting Problem on Evolving Data[J]. ALGORITHMICA,2017,79(3):960-983.
APA	Huang, Qin,Liu, Xingwu,Sun, Xiaoming,&Zhang, Jialin.(2017).Partial Sorting Problem on Evolving Data.ALGORITHMICA,79(3),960-983.
MLA	Huang, Qin,et al."Partial Sorting Problem on Evolving Data".ALGORITHMICA 79.3(2017):960-983.