Please wait a minute...
文章检索
复杂系统与复杂性科学  2017, Vol. 14 Issue (2): 103-109    DOI: 10.13306/j.1672-3813.2017.02.015
  本期目录 | 过刊浏览 | 高级检索 |
基于空间活跃度网络的搜索策略研究
韩定定, 柳康, 陈超, 陈趣
华东师范大学上海市多维度信息处理重点实验室,上海 200241
Search Strategies Based on Spatial Activity Network
HAN Dingding, LIU Kang, CHEN Chao, CHEN Qu
Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai 200241, China
全文: PDF(927 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 基于具有时变特性与空间特性的空间活跃度网络模型,研究了时变网络中的搜索问题。结合空间活跃度网络的特性,引入了搜索时间、搜索路径长度和等待时间3种搜索策略的评价指标,提出了最大活跃度搜索策略、改进的贪婪搜索策略和最大活跃度最小距离搜索策略。利用这些策略在空间活跃度网络中进行搜索,研究发现和其他的搜索策略相比,改进的贪婪搜索策略与最大活跃度最小距离搜索策略具有较好的搜索性能,能够很好地适用于这种类型的时变网络,从而优化了目标搜索的过程。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
韩定定
柳康
陈超
陈趣
关键词 时变网络活跃度驱动空间性搜索策略最优搜索    
Abstract:Based on spatial activity network with the characteristics oftime varying and spatial property, searching on time varying network was studied in this paper. Combined with the characteristics of spatial activity network, search time, search path length and waiting time were introduced as evaluation indexes for search strategy. And maximum activity searching strategy, improved greedy searching strategy and maximum activity minimum distance searching strategy were proposed. It was found that using improved greedy searching strategy and maximum activity minimum distance searching strategy to search on the spatial activity network would get higher efficiency than any of other strategies. They were suitable for this type of time varying network and able to optimize the searching process.
Key wordstime varying network    activity driven    spatial property    searching strategies    optimal searching
收稿日期: 2016-11-01      出版日期: 2025-02-25
ZTFLH:  TP393.2  
作者简介: 韩定定(1968-),女,上海人,博士,教授,主要研究方向为复杂网络与智能信息处理。
引用本文:   
韩定定, 柳康, 陈超, 陈趣. 基于空间活跃度网络的搜索策略研究[J]. 复杂系统与复杂性科学, 2017, 14(2): 103-109.
HAN Dingding, LIU Kang, CHEN Chao, CHEN Qu. Search Strategies Based on Spatial Activity Network[J]. Complex Systems and Complexity Science, 2017, 14(2): 103-109.
链接本文:  
https://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2017.02.015      或      https://fzkx.qdu.edu.cn/CN/Y2017/V14/I2/103
[1] Watts D J, Strogatz S H. Collective dynamics of “small-world” networks[J].Nature, 1998, 393(6684):440-442.
[2] Liljeros F, Edling C R, Lan A. The web of human sexual contacts[J].Nature, 2001, 411(6840):907-908.
[3] Ebel H, Mielsch L I, Bornholdt S. Scale-free topology of e-mail networks[J].Physical Review E, 2002, 66(3):035103.
[4] Holme P, Saramäki J. Temporal networks[J].Physics Reports, 2012, 519(3):97-125.
[5] Bearman P S, Moody J, Stovel K. Chains of affection: the structure of adolescent romantic and sexual networks[J].American journal of sociology, 2004, 110(1): 44-91.
[6] Cheng E, Grossman J W, Lipman M J. Time-stamped graphs and their associated influence digraphs[J].Discrete Applied Mathematics, 2003, 128(2): 317-335.
[7] Riolo C S, Koopman J S, Chick S E. Methods and measures for the description of epidemiologic contact networks[J].Journal of Urban Health, 2001, 78(3): 446-457.
[8] Pan R K, Saramäki J. Path lengths, correlations, and centrality in temporal networks[J].Physical Review E, 2011, 84(1): 016105.
[9] Tang J, Musolesi M, Mascolo C, et al. Temporal distance metrics for social network analysis[C].Proceedings of the 2nd ACM Workshop on Online Social Networks. ACM, 2009: 31-36.
[10] Xuan B B, Ferreira A, Jarry A. Computing shortest, fastest, and foremost journeys in dynamic networks[J].International Journal of Foundations of Computer Science, 2003, 14(2): 267-285.
[11] Holme P, Edling C R, Liljeros F. Structure and time evolution of an Internet dating community[J].Social Networks, 2004, 26(2):155-174.
[12] Medo M, Cimini G, Gualdi S. Temporal effects in the growth of networks[J].Physical review letters, 2011, 107(23): 238701.
[13] Chen Q, Han D D, Qian J H, et al. Optimal temporal path on spatial decaying networks[J].Journal of Applied Analysis and Computation, 2016, 6(1):30-37.
[14] Chen Q, Qian J H, Zhu L, et al. Optimal transport in time-varying small-world networks[J].Physical Review E, 2016, 93(3): 032321.
[15] Perra N, Gon?alves B, Pastor-Satorras R, et al. Activity driven modeling of time varying networks[J].Scientific Reports, 2012, 2(6):1717-1720.
[16] Milgram S. The small world problem[J].Psychology Today, 1967, 2(1):185-195.
[17] Pandit S A, Amritkar R E. Random spread on the family of small-world networks[J].Physical Review E, 2001, 63(4): 041104.
[18] Adamic L A, Lukose R M, Huberman B A. Local search in unstructured networks[J].Handbook of Graphs & Networks, 2002:295-317.
[19] Adamic L A, Lukose R M, Puniyani A R, et al. Search in power-law networks[J].Physical review E, 2001, 64(4): 046135.
[20] Kleinberg J M. Navigation in a small world[J].Nature, 2000, 41(10):2496-2515.
[21] Echenique P, Gómez-Gardees J, Moreno Y. Improved routing strategies for Internet traffic delivery[J].Physical Review E, 2004, 70(5): 056105.
No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed