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Time-topology analysis on temporal graphs 时间图的时间拓扑分析
IF 4.2 2区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2023-01-06 DOI: 10.1007/s00778-022-00772-y
Yunkai Lou, Chaokun Wang, Tiankai Gu, Hao Feng, Jun Chen, J. Yu
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引用次数: 1
Making graphs compact by lossless contraction. 通过无损收缩使图形紧凑
IF 2.8 2区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2023-01-01 Epub Date: 2022-02-19 DOI: 10.1007/s00778-022-00731-7
Wenfei Fan, Yuanhao Li, Muyang Liu, Can Lu

This paper proposes a scheme to reduce big graphs to small graphs. It contracts obsolete parts and regular structures into supernodes. The supernodes carry a synopsis S Q for each query class Q in use, to abstract key features of the contracted parts for answering queries of Q . Moreover, for various types of graphs, we identify regular structures to contract. The contraction scheme provides a compact graph representation and prioritizes up-to-date data. Better still, it is generic and lossless. We show that the same contracted graph is able to support multiple query classes at the same time, no matter whether their queries are label based or not, local or non-local. Moreover, existing algorithms for these queries can be readily adapted to compute exact answers by using the synopses when possible and decontracting the supernodes only when necessary. As a proof of concept, we show how to adapt existing algorithms for subgraph isomorphism, triangle counting, shortest distance, connected component and clique decision to contracted graphs. We also provide a bounded incremental contraction algorithm in response to updates, such that its cost is determined by the size of areas affected by the updates alone, not by the entire graphs. We experimentally verify that on average, the contraction scheme reduces graphs by 71.9% and improves the evaluation of these queries by 1.69, 1.44, 1.47, 2.24 and 1.37 times, respectively.

本文提出了一种将大图缩减为小图的方案。它将过时的部分和规则结构收缩为超级节点。超级节点为每个正在使用的查询类 Q 携带一个概要 S Q,以抽象出用于回答 Q 查询的收缩部分的关键特征。此外,对于各种类型的图,我们会确定需要收缩的规则结构。收缩方案提供了一种紧凑的图表示法,并优先处理最新数据。更妙的是,它具有通用性和无损性。我们证明,同一个收缩图能够同时支持多个查询类别,无论它们的查询是否基于标签,是本地查询还是非本地查询。此外,针对这些查询的现有算法可以很容易地进行调整,在可能的情况下使用概要,只有在必要时才去收缩上节点,从而计算出精确的答案。作为概念证明,我们展示了如何将现有的子图同构、三角形计数、最短距离、连通组件和簇判定算法调整到收缩图上。我们还针对更新提供了一种有界增量收缩算法,其成本仅由受更新影响的区域大小决定,而不是由整个图决定。我们通过实验验证了收缩方案平均减少了 71.9% 的图,并将这些查询的评估结果分别提高了 1.69、1.44、1.47、2.24 和 1.37 倍。
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引用次数: 0
ProS: data series progressive k-NN similarity search and classification with probabilistic quality guarantees 优点:具有概率质量保证的数据序列渐进式k-NN相似性搜索和分类
IF 4.2 2区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2022-11-30 DOI: 10.1007/s00778-022-00771-z
Karima Echihabi, Theophanis Tsandilas, Anna Gogolou, A. Bezerianos, Themis Palpanas
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引用次数: 9
A generic framework for efficient computation of top-k diverse results 一种高效计算top-k不同结果的通用框架
IF 4.2 2区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2022-11-28 DOI: 10.1007/s00778-022-00770-0
Md Mouinul Islam, Mahsa Asadi, S. Amer-Yahia, Senjuti Basu Roy
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引用次数: 1
Augmented lineage: traceability of data analysis including complex UDF processing 增强谱系:数据分析的可追溯性,包括复杂的UDF处理
IF 4.2 2区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2022-11-23 DOI: 10.1007/s00778-022-00769-7
Masaya Yamada, H. Kitagawa, T. Amagasa, Akiyoshi Matono
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引用次数: 0
P2CG: a privacy preserving collaborative graph neural network training framework P2CG:一个隐私保护协同图神经网络训练框架
IF 4.2 2区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2022-11-04 DOI: 10.1007/s00778-022-00768-8
Xupeng Miao, Wentao Zhang, Yuezihan Jiang, Fangcheng Fu, Yingxia Shao, Lei Chen, Yangyu Tao, Gang-Ming Cao, Bin Cui
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引用次数: 2
Practical planning and execution of groupjoin and nested aggregates 组连接和嵌套聚合的实际规划和执行
IF 4.2 2区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2022-10-22 DOI: 10.1007/s00778-022-00765-x
Philipp Fent, Altan Birler, Thomas Neumann
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引用次数: 1
PARROT: pattern-based correlation exploitation in big partitioned data series PARROT:大分区数据序列中基于模式的相关性挖掘
IF 4.2 2区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2022-10-13 DOI: 10.1007/s00778-022-00767-9
Liang Zhang, Noura A. Alghamdi, Huayi Zhang, M. Eltabakh, Elke A. Rundensteiner
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引用次数: 2
Special issue on the best papers of DaMoN 2020 DaMoN 2020最佳论文特刊
IF 4.2 2区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2022-10-07 DOI: 10.1007/s00778-022-00766-w
Danica Porobic
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引用次数: 0
Toward maintenance of hypercores in large-scale dynamic hypergraphs 大规模动态超图中超核的维护
IF 4.2 2区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE Pub Date : 2022-09-20 DOI: 10.1007/s00778-022-00763-z
Qi Luo, Dongxiao Yu, Z. Cai, Xuemin Lin, Guanghui Wang, Xiuzhen Cheng
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引用次数: 4
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