Abstract
Science of the Crowd is a new paradigm. The research on the relationship between provision and demand arising from the behavior of the crowd under the interconnected environment is a promising topic. This study is a pioneer work on the establishment of a new type of interconnected architecture - rim chain. The rim chain framework aims at supporting prompt matching between provision and requirements. The analytical results suggest that requirements can be fulfilled in accordance with six degrees of separation. In other word, the matching between the demands and provision takes place with six hops in the rim chain framework. Improved top-k method is employed to obtain the matching results. Last but not least, the efficiency of the method is validated.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Li, W., Wu, W., Wang, H., et al.: Crowd intelligence in AI 2.0 era. Front. Inf. Technol. Electron. Eng. 18(1), 15–43 (2017)
Pierre, L.: Collective Intelligence: Mankind’s Emerging World in Cyberspace. Perseus Books, Cambrigde (1997)
Lévy, P.: Collective Intelligence. Plenum/Harper Collins, New York (1997)
Kutsenok, A., Swarm, A.I.: A solution to soccer. Master’s thesis, Department of Computer Science, Rose-Hulman Institute of Technology, Terre Haute, IN (2004)
Chai, Y., Miao, C., Sun, B., et al.: Crowd science and engineering: concept and research framework. Int. J. Crowd Sci. 1(1), 2–8 (2017)
Jiahui, J., Khemmarat, S., Gao, L., et al.: A distributed approach for top-k star queries on massive information networks. In: IEEE International Conference on Parallel and Distributed Systems, Southeast Univ., Nanjing, China, pp. 9–16 (2014)
Chen, S., Wang, J.: Keyword distributed search with ontology subgraph over RDF data. J. Fuzhou Univ. (Nat. Sci. Ed.) 45(06), 822–828+845 (2017)
Yu, S.: Research on object-level keyword search algorithm over graph database. Chap. 3, Ph.D. thesis, Department of Computer Science, Dalian Maritime University (2013)
Li, X., et al.: A novel graph containment query algorithm on graph databases. J. Digit. Inf. Manag. 7(3), 143–151 (2009)
Chen, Z., Li, S., Liu, W.: Range-constrained Top-k keyword query on road networks. J. Chin. Comput. Syst. 38(12), 2707–2713 (2017)
Yang, Z., Si, Y., Li, Z., et al.: ARE: new conceptual model for social crowd behavior modeling. J. Syst. Simul. 24(02), 435–440 (2012)
Morgan, T.J., et al.: Experimental evidence for the co-evolution of hominin tool-making teaching and language. Nat. Commun. 6, 6029–6029 (2015)
Nicholas, A., James, H.: Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives. Simon & Schuster Audio, Abridged (2009)
Meng, J., Chen, L., Ma, W., et al.: Research and application on similarity search algorithm in graph database. Appl. Res. Comput. 27(05), 1813–1815+1819 (2010)
Zhang, Z., Xia, D., Xie, X., et al.: A keyword search method for graphs by considering content and structure. J. Comput. Aided Des. Comput. Graph. 27(11), 2211–222 (2015)
Sun, L., Liu, Y., Bartolacci, M.R., et al.: A multi information dissemination model considering the interference of derivative information. Phys. Stat. Mech. Appl. 451, 541–548 (2016)
Liang, Z., Xu, B., Jia, Y., et al.: Online link strength trend model based on content and topology. In: 2011 International Symposium on Image and Data Fusion (ISIDF), pp. 1–5. IEEE (2011)
Li, X., Liu, Y., Jing, K., et al.: The influence of the timeheterogeneity of nodes on the information dissemination. Syst. Sci. Math. Sci. 36(10), 1630–1642 (2016)
Wang, Z., Chen, E., Liu, Q., et al.: Maximizing the coverage of information propagation in social networks. In: International Conference on Artificial Intelligence, pp. 2104–2110. AAAI Press (2015)
Fang, J., Li, Y.: Advances in unified hybrid theoretical model of network science. Adv. Mech. 06, 663–678 (2008)
Huang, H., Jaing, A., Hu, M.: Analysis of information diffusion model on social network. Appl. Res. Comput. 33(09), 2738–2742 (2016)
Acknowledgements
This work is partially supported by National Key R&D Program No. 2017YFB1400100.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendix
Appendix
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Li, P., Liu, L., Cui, L., Li, Q., Zheng, Y., Zhou, G. (2018). Rim Chain: Bridge the Provision and Demand Among the Crowd. In: Vaidya, J., Li, J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2018. Lecture Notes in Computer Science(), vol 11335. Springer, Cham. https://doi.org/10.1007/978-3-030-05054-2_2
Download citation
DOI: https://doi.org/10.1007/978-3-030-05054-2_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-05053-5
Online ISBN: 978-3-030-05054-2
eBook Packages: Computer ScienceComputer Science (R0)