Titlebook: Complex Networks and Their Applications VII; Volume 2 Proceedings Luca Maria Aiello,Chantal Cherifi,Luis M. Rocha Conference proceedings 20

Blandishment

書目名稱Complex Networks and Their Applications VII影響因子(影響力)




書目名稱Complex Networks and Their Applications VII影響因子(影響力)學(xué)科排名




書目名稱Complex Networks and Their Applications VII網(wǎng)絡(luò)公開度




書目名稱Complex Networks and Their Applications VII網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Complex Networks and Their Applications VII被引頻次




書目名稱Complex Networks and Their Applications VII被引頻次學(xué)科排名




書目名稱Complex Networks and Their Applications VII年度引用




書目名稱Complex Networks and Their Applications VII年度引用學(xué)科排名




書目名稱Complex Networks and Their Applications VII讀者反饋




書目名稱Complex Networks and Their Applications VII讀者反饋學(xué)科排名

HAVOC

Analysis of the Web Graph Aggregated by Host and Pay-Level Domainased by the Common Crawl Foundation?(.) and are based on a web crawl performed during the period May-June-July 2017. The host graph has .1.3 billion nodes and .5.3 billion arcs. The PLD graph has .91 million nodes and .1.1 billion arcs. We study the distributions of degree and sizes of strongly/weak

MULTI

Characterizing Temporal Bipartite Networks - Sequential- Versus Cross-Taskingllows us to explore user behavior in-depth. We propose two metrics, the relative switch frequency and distraction in time to measure a user’s sequential-tasking level, i.e. to what extent a user interacts with a task consecutively without interacting with other tasks in between. We analyze the seque

SUGAR

珠寶

Spectral Measures of Distortion for Change Detection in Dynamic Graphs, which can be sensitive to minor and isolated changes, and are often based on heuristics, we show how a theoretically-justified, inherently multi-scale notion of change, or distortion, can be defined and computed using spectral graph-theoretic tools. Our primary observation is that informative, rob

極深

極深

The Impact of Indirect Connections: The Case of Food Security Problemnections between nodes. We reward edges that increase node-to-node influence compared to direct connections between them. This approach allows to reveal hidden channels of the influence in networks. We apply the proposed model to food export/import networks in order to elucidate the most important t

不可知論

A Compressive Sensing Framework for Distributed Detection of High Closeness Centrality Nodes in Netw algorithms require a node to only have local interactions with its immediate neighbors. This is due to the fact that the whole network topology is usually unknown to each individual node. Detecting key actors within a network with respect to different notions of influence, has recently received a l

disrupt

的’

: A Scalable Multiplex Network Embedding Frameworktwork-based machine learning tasks like node classification, link prediction, and network alignment. However, very few methods focus on capturing representations for . networks, which are more accurate and detailed representations of complex networks. In this work, we propose . a fast and scalable e