中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Parameterized Dynamic Cluster Editing

文献类型:期刊论文

作者Luo, Junjie2,3; Molter, Hendrik1; Nichterlein, Andre1; Niedermeier, Rolf1
刊名ALGORITHMICA
出版日期2020-07-25
页码44
ISSN号0178-4617
关键词Graph-based data clustering Incremental clustering Compromise clustering Correlation clustering Local search Goal-oriented clustering NP-hard problems Fixed-parameter tractability Parameterized complexity Kernelization Multi-choice knapsack
DOI10.1007/s00453-020-00746-y
英文摘要We introduce a dynamic version of the NP-hard graph modification problemCluster Editing. The essential point here is to take into account dynamically evolving input graphs: having a cluster graph (that is, a disjoint union of cliques) constituting a solution for a first input graph, can we cost-efficiently transform it into a "similar" cluster graph that is a solution for a second ("subsequent") input graph? This model is motivated by several application scenarios, including incremental clustering, the search for compromise clusterings, or also local search in graph-based data clustering. We thoroughly study six problem variants (three modification scenarios edge editing, edge deletion, edge insertion; each combined with two distance measures between cluster graphs). We obtain both fixed-parameter tractability as well as (parameterized) hardness results, thus (except for three open questions) providing a fairly complete picture of the parameterized computational complexity landscape under the two perhaps most natural parameterizations: the distances of the new "similar" cluster graph to (1) the second input graph and to (2) the input cluster graph.
资助项目Projekt DEAL ; CAS-DAAD Joint Fellowship Program of UCAS ; DFG, Project AFFA[BR 5207/1] ; DFG, Project MATE[NI 369/17]
WOS研究方向Computer Science ; Mathematics
语种英语
出版者SPRINGER
WOS记录号WOS:000552516200002
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/51888]  
专题中国科学院数学与系统科学研究院
通讯作者Molter, Hendrik
作者单位1.TU Berlin, Fac 4, Algorithm & Computat Complex, Berlin, Germany
2.Univ Chinese Acad Sci, Sch Math Sci, Beijing, Peoples R China
3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
推荐引用方式
GB/T 7714
Luo, Junjie,Molter, Hendrik,Nichterlein, Andre,et al. Parameterized Dynamic Cluster Editing[J]. ALGORITHMICA,2020:44.
APA Luo, Junjie,Molter, Hendrik,Nichterlein, Andre,&Niedermeier, Rolf.(2020).Parameterized Dynamic Cluster Editing.ALGORITHMICA,44.
MLA Luo, Junjie,et al."Parameterized Dynamic Cluster Editing".ALGORITHMICA (2020):44.

入库方式: OAI收割

来源:数学与系统科学研究院

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