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Random graph theory 2 Complex network 1 Degree distribution 1 Energy consumption 1 Eulerian graph 1 Model 1 Wireless sensor networks 1 collaborative filtering 1 consumer-purchase behavior 1 random graph theory 1 recommender systems 1 topological features 1 π 1
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Undetermined 3
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Article 3
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Chen, Guanrong 1 Chen, Hsinchun 1 Ding, Li 1 Guan, Zhi-Hong 1 Huang, Zan 1 Lui, Kenneth W.K. 1 So, H.C. 1 Zeng, Daniel D. 1
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Physica A: Statistical Mechanics and its Applications 2 Management Science 1
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RePEc 3
Showing 1 - 3 of 3
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The π sequence as a complex network
Lui, Kenneth W.K.; So, H.C.; Chen, Guanrong - In: Physica A: Statistical Mechanics and its Applications 387 (2008) 22, pp. 5653-5661
In this paper, a new topological approach for studying a sufficiently long random number sequence is proposed. By segmenting the sequence into groups of digits which represent the node identities while the undirected edges symbolize the adjacency between them, a network is constructed for...
Persistent link: https://www.econbiz.de/10011058276
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Modeling wireless sensor networks using random graph theory
Ding, Li; Guan, Zhi-Hong - In: Physica A: Statistical Mechanics and its Applications 387 (2008) 12, pp. 3008-3016
A critical issue in wireless sensor networks (WSNs) is represented by limited availability of energy within network nodes. Therefore, making good use of energy is necessary in modeling sensor networks. In this paper we proposed a new model of WSNs on a two-dimensional plane using site...
Persistent link: https://www.econbiz.de/10010590982
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Analyzing Consumer-Product Graphs: Empirical Findings and Applications in Recommender Systems
Huang, Zan; Zeng, Daniel D.; Chen, Hsinchun - In: Management Science 53 (2007) 7, pp. 1146-1164
We apply random graph modeling methodology to analyze bipartite consumer-product graphs that represent sales transactions to better understand consumer purchase behavior in e-commerce settings. Based on two real-world e-commerce data sets, we found that such graphs demonstrate topological...
Persistent link: https://www.econbiz.de/10009191395
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