標(biāo)題: Titlebook: Algorithms and Models for the Web Graph; 16th International W Konstantin Avrachenkov,Pawe? Pra?at,Nan Ye Conference proceedings 2019 Spring [打印本頁] 作者: lutein 時(shí)間: 2025-3-21 18:48
書目名稱Algorithms and Models for the Web Graph影響因子(影響力)
書目名稱Algorithms and Models for the Web Graph影響因子(影響力)學(xué)科排名
書目名稱Algorithms and Models for the Web Graph網(wǎng)絡(luò)公開度
書目名稱Algorithms and Models for the Web Graph網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Algorithms and Models for the Web Graph被引頻次
書目名稱Algorithms and Models for the Web Graph被引頻次學(xué)科排名
書目名稱Algorithms and Models for the Web Graph年度引用
書目名稱Algorithms and Models for the Web Graph年度引用學(xué)科排名
書目名稱Algorithms and Models for the Web Graph讀者反饋
書目名稱Algorithms and Models for the Web Graph讀者反饋學(xué)科排名
作者: DEVIL 時(shí)間: 2025-3-21 20:42
A Spatial Small-World Graph Arising from Activity-Based Reinforcement,ndom graph model in a spatial setting, where such a time-variability arises from an activity-based reinforcement mechanism. We show that the reinforcement mechanism converges, and prove rigorously that the resulting random graph exhibits the small-world property. A further motivation for this random graph stems from modeling synaptic plasticity.作者: 手段 時(shí)間: 2025-3-22 01:49 作者: SKIFF 時(shí)間: 2025-3-22 04:40
Algorithms and Models for the Web Graph978-3-030-25070-6Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: nuclear-tests 時(shí)間: 2025-3-22 11:21
John Tyndall,H. Helmholtz,G. WiedemannHere we consider both deterministic and probabilistic methods to produce .-ordered countable graphs with universal adjacency properties. In the countably infinite case, we show that such universal adjacency properties imply the existence an independent 2-distinguishing labelling.作者: 宣稱 時(shí)間: 2025-3-22 13:08 作者: 笨拙的你 時(shí)間: 2025-3-22 19:18 作者: athlete’s-foot 時(shí)間: 2025-3-22 21:28 作者: 我不死扛 時(shí)間: 2025-3-23 04:23 作者: mastopexy 時(shí)間: 2025-3-23 08:11 作者: ALLAY 時(shí)間: 2025-3-23 09:54
https://doi.org/10.1007/978-3-476-03979-8 such software by walking around the vertices of a graph. Once initial random vertex weights have been assigned, the robot crawler traverses the graph deterministically following a greedy algorithm, always visiting the neighbour of least weight and then updating this weight to be the highest overall作者: 使苦惱 時(shí)間: 2025-3-23 17:13 作者: gerontocracy 時(shí)間: 2025-3-23 20:29 作者: LAVE 時(shí)間: 2025-3-24 01:08
https://doi.org/10.1007/978-3-322-90287-0ndom graph model in a spatial setting, where such a time-variability arises from an activity-based reinforcement mechanism. We show that the reinforcement mechanism converges, and prove rigorously that the resulting random graph exhibits the small-world property. A further motivation for this random作者: Cpap155 時(shí)間: 2025-3-24 03:18 作者: 描述 時(shí)間: 2025-3-24 07:09 作者: 拋媚眼 時(shí)間: 2025-3-24 13:52 作者: 否決 時(shí)間: 2025-3-24 16:15
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/153180.jpg作者: 僵硬 時(shí)間: 2025-3-24 20:03
0302-9743 cover topics of all aspects of algorithmic and mathematical research in the areas pertaining to the World Wide Web, espousing the view of complex data as networks..978-3-030-25069-0978-3-030-25070-6Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 緩解 時(shí)間: 2025-3-25 01:14
Darstellungsmethoden des Sauerstoffes,esults with statistical methods shows that a number of transformed proximity measures outperform their non-transformed versions. The top-performing transformed measures are the Heat measure transformed with the power function, the Forest measure transformed with the power function, and the Forest measure transformed with the logarithmic function.作者: 小平面 時(shí)間: 2025-3-25 06:44 作者: 付出 時(shí)間: 2025-3-25 10:55
,Forschungsans?tze und -ertr?ge,n of formal estimators for these graphs, and a new Maximum Likelihood Estimator with .(.) computational complexity where . is the number of edges in the graph, and requiring only link lengths as input, as compared to all other algorithms which are ..作者: 鋼盔 時(shí)間: 2025-3-25 11:45 作者: 聯(lián)想 時(shí)間: 2025-3-25 19:04
https://doi.org/10.1007/978-3-663-20181-6-supervised learning works very well. Specifically, for the Stochastic Block Model in the moderately sparse regime, we prove that popular semi-supervised clustering methods like Label Spreading achieve asymptotically almost exact recovery as long as the fraction of labeled nodes does not go to zero and the average degree goes to infinity.作者: 逃避責(zé)任 時(shí)間: 2025-3-25 22:05 作者: Inoperable 時(shí)間: 2025-3-26 02:07 作者: 良心 時(shí)間: 2025-3-26 07:48
,The Robot Crawler Model on Complete k-Partite and Erd?s-Rényi Random Graphs,. We consider the maximum, minimum and average number of steps taken by the crawler to visit every vertex of firstly, sparse Erd?s-Rényi random graphs and secondly, complete k-partite graphs. Our work is closely related to a paper of Bonato et al. who introduced the model.作者: milligram 時(shí)間: 2025-3-26 10:07 作者: 我要沮喪 時(shí)間: 2025-3-26 16:20
,Schlu?folgerungen und Ausblick,tiveness of the reduction rules is independent of the underlying graph structure. Finally, we show that high locality is also prevalent in instances from other domains, facilitating a fast computation of minimum hitting sets.作者: 燒瓶 時(shí)間: 2025-3-26 18:00 作者: RECUR 時(shí)間: 2025-3-26 22:24 作者: 去才蔑視 時(shí)間: 2025-3-27 03:51 作者: 高度表 時(shí)間: 2025-3-27 05:34 作者: 說笑 時(shí)間: 2025-3-27 11:52
Using Synthetic Networks for Parameter Tuning in Community Detection,ructural properties and communities of various nature. As a result, it is hard (or even impossible) to develop one algorithm suitable for all datasets. A standard machine learning tool is to consider a parametric algorithm and choose its parameters based on the dataset at hand. However, this approac作者: 修飾 時(shí)間: 2025-3-27 15:20
Efficiency of Transformations of Proximity Measures for Graph Clustering,formed with a number of functions including the logarithmic function, the power function, and a family of activation functions. Transformations are tested in experiments in which several classical datasets are clustered using the .-Means, Ward, and the spectral method. The analysis of experimental r作者: 飛來飛去真休 時(shí)間: 2025-3-27 18:34
Almost Exact Recovery in Label Spreading,ve high accuracy clustering using efficient computational procedures. Our main goal is to provide a theoretical justification why the graph-based semi-supervised learning works very well. Specifically, for the Stochastic Block Model in the moderately sparse regime, we prove that popular semi-supervi作者: Acetaldehyde 時(shí)間: 2025-3-28 01:21 作者: lambaste 時(shí)間: 2025-3-28 03:34 作者: 凝視 時(shí)間: 2025-3-28 09:48
Estimating the Parameters of the Waxman Random Graph, thus less numerous. The model has been in continuous use for over three decades with many attempts to match parameters to real networks, but only a few cases where a formal estimator was used. Even then the performance of the estimator was not evaluated. This paper presents both the first evaluatio作者: cringe 時(shí)間: 2025-3-28 12:33
Understanding the Effectiveness of Data Reduction in Public Transportation Networks, a selected station. Although this problem is NP-hard in general, real-world instances are regularly solved almost completely by a set of simple reduction rules. To explain this behavior, we view transportation networks as hitting set instances and identify two characteristic properties, locality an作者: 煩人 時(shí)間: 2025-3-28 17:38
A Spatial Small-World Graph Arising from Activity-Based Reinforcement,ndom graph model in a spatial setting, where such a time-variability arises from an activity-based reinforcement mechanism. We show that the reinforcement mechanism converges, and prove rigorously that the resulting random graph exhibits the small-world property. A further motivation for this random
