constellation
发表于 2025-3-25 04:20:33
Conference proceedings 2009na, Spain, in February 2009 - co-located with WSDM 2009, the Second ACM International Conference on Web Search and Data Mining. The 14 revised full papers presented were carefully reviewed and selected from numerous submissions for inclusion in the book. The papers address a wide variety of topics r
手榴弹
发表于 2025-3-25 09:43:38
0302-9743 in Barcelona, Spain, in February 2009 - co-located with WSDM 2009, the Second ACM International Conference on Web Search and Data Mining. The 14 revised full papers presented were carefully reviewed and selected from numerous submissions for inclusion in the book. The papers address a wide variety o
Generator
发表于 2025-3-25 13:38:45
https://doi.org/10.1007/978-3-662-29141-2 higher moments of its degree sequence. We define the second order average degree . to be . where .. denotes the degree of .. We prove that for any .> 0, if . then asymptotically almost surely the percolated subgraph .. has a giant component. In the other direction, if . then almost surely the percolated subgraph .. contains no giant component.
CHURL
发表于 2025-3-25 17:40:43
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低三下四之人
发表于 2025-3-25 21:05:01
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DRILL
发表于 2025-3-26 03:07:19
The Giant Component in a Random Subgraph of a Given Graph higher moments of its degree sequence. We define the second order average degree . to be . where .. denotes the degree of .. We prove that for any .> 0, if . then asymptotically almost surely the percolated subgraph .. has a giant component. In the other direction, if . then almost surely the percolated subgraph .. contains no giant component.
官僚统治
发表于 2025-3-26 06:07:51
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琐碎
发表于 2025-3-26 10:29:24
Cluster Based Personalized Searchome formal criteria for evaluating such personalized ranking algorithms and provide some preliminary experiments in support of our analysis. Both theoretically and experimentally, our algorithm differs significantly from Topc Sensitive Page Rank.
BROOK
发表于 2025-3-26 14:10:55
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硬化
发表于 2025-3-26 20:12:17
https://doi.org/10.1007/978-3-662-29141-2data sets obtained from Internet Archive, Wikipedia and Yahoo! ranking lists. We also study the temporal robustness of the prediction framework. Overall the system constitutes a set of tools for high accuracy pagerank prediction which can be used for efficient resource management by search engines.