Abstract
In the current era of big data, huge volumes of a wide variety of valuable data of different veracity (e.g., uncertain data) can be easily collected and generated from a broad range of data sources (e.g., social networking sites) at a high velocity in various real-life applications. Many traditional data management and analytic approaches may not be suitable for handling the big data due to their well-known 5V’s characteristics. In this paper, we present a cognitive-based system for social network analysis. Our system supports information discovery of interesting social patterns from big uncertain social networks—which are represented in the form of key-value pairs—capturing the perceived likelihood of the linkages among the social entities in the network.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Abu-Salih, B., Wongthongtham, P., Zhu, D., Alqrainy, S.: An approach for time-aware domain-based analysis of users’ trustworthiness in big social data. IJBD (now STBD) 2(1), 41–56 (2015)
Braun, P., Cameron, J.J., Cuzzocrea, A., Jiang, F., Leung, C.K.: Effectively and efficiently mining frequent patterns from dense graph streams on disk. Procedia Comput. Sci. 35, 338–347 (2014)
Braun, P., Cuzzocrea, A., Jiang, F., Leung, C.K.-S., Pazdor, A.G.M.: MapReduce-based complex big data analytics over uncertain and imprecise social networks. In: Bellatreche, L., Chakravarthy, S. (eds.) DaWaK 2017. LNCS, vol. 10440, pp. 130–145. Springer, Cham (2017)
Braun, P., Cuzzocrea, A., Leung, C.K., Pazdor, A.G.M., Tanbeer, S.K.: Mining frequent patterns from IoT devices with fog computing. In: HPCS 2017, pp. 691–698 (2017)
Braun, P., Cuzzocrea, A., Leung, C.K., Pazdor, A., Tran, K.: Knowledge discovery from social graph data. Procedia Comput. Sci. 96, 682–691 (2016)
Chen, I., Guo, J., Tsai, J.J.P.: Trust as a service for SOA-based IoT systems. STIOT 1(1), 43–52 (2017)
Chen, J., Yang, Y.: Grid and workflows. In: Encyclopedia of Database Systems, 2nd edn. (2016). https://doi.org/10.1007/978-1-4899-7993-3_1472-2
Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms, 3rd edn. MIT Press, Cambridge (2009)
Cuzzocrea, A.: Accuracy control in compressed multidimensional data cubes for quality of answer-based OLAP tools. In: SSDBM 2006, pp. 301–310 (2006)
Cuzzocrea, A.: Privacy and security of big data: current challenges and future research perspectives. In: PSBD 2014, pp. 45–47 (2014)
Cuzzocrea, A., Bertino, E.: A secure multiparty computation privacy preserving OLAP framework over distributed XML data. In: ACM SAC 2010, pp. 1666–1673 (2010)
Cuzzocrea, A., Bertino, E.: Privacy preserving OLAP over distributed XML data: a theoretically-sound secure-multiparty-computation approach. JCSS 77(6), 965–987 (2011)
Cuzzocrea, A., Furfaro, F., Saccà, D.: Enabling OLAP in mobile environments via intelligent data cube compression techniques. JISS 33(2), 95–143 (2009)
Cuzzocrea, A., Han, Z., Jiang, F., Leung, C.K., Zhang, H.: Edge-based mining of frequent subgraphs from graph streams. Procedia Comput. Sci. 60, 573–582 (2015)
Cuzzocrea, A., Lee, W., Leung, C.K.: High-recall information retrieval from linked big data. In: IEEE COMPSAC 2015, vol. 2, pp. 712–717 (2015)
Cuzzocrea, A., Leung, C.K.: Upper bounds to expected support for frequent itemset mining of uncertain big data. In: ACM SAC 2015, pp. 919–921 (2015)
Cuzzocrea, A., Matrangolo, U.: Analytical synopses for approximate query answering in OLAP environments. In: Galindo, F., Takizawa, M., Traunmüller, R. (eds.) DEXA 2004. LNCS, vol. 3180, pp. 359–370. Springer, Heidelberg (2004)
Han, Z., Leung, C.K.: FIMaaS: scalable frequent pattern mining-as-a-service on cloud for non-expert miners. In: BigDAS 2015, pp. 84–91 (2015)
Jiang, F., Leung, C.K., Liu, D.: Efficiency improvements in social network communication via MapReduce. In: IEEE DSDIS 2015, pp. 161–168 (2015)
Kawagoe, K., Leung, C.K.: Similarities of frequent following patterns and social entities. Procedia Comput. Sci. 60, 642–651 (2015)
Lahoti, P., Garimella, K., Gionis, A.: Joint non-negative matrix factorization for learning ideological leaning on Twitter. In: ACM WSDM 2018, pp. 351–359 (2018)
Leung, C.K.: Big data mining applications and services. In: BigDAS 2015, pp. 1–8 (2015)
Leung, C.K., Braun, P., Enkhee, M., Pazdor, A.G.M., Sarumi, O.A., Tran, K.: Knowledge discovery from big social key-value data. In: IEEE CIT 2016, pp. 484–491 (2016)
Leung, C.K., Cuzzocrea, A.: Frequent subgraph mining from streams of uncertain data. In: C3S2E 2015, pp. 18–27 (2015)
Leung, C.K.-S., Hayduk, Y.: Mining frequent patterns from uncertain data with mapreduce for big data analytics. In: Meng, W., Feng, L., Bressan, S., Winiwarter, W., Song, W. (eds.) DASFAA 2013, Part I. LNCS, vol. 7825, pp. 440–455. Springer, Heidelberg (2013)
Leung, C.K.-S., Jiang, F.: Big data analytics of social networks for the discovery of “Following” patterns. In: Madria, S., Hara, T. (eds.) DaWaK 2015. LNCS, vol. 9263, pp. 123–135. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-22729-0_10
Leung, C.K., Jiang, F., Pazdor, A.G.M., Peddle, A.M.: Parallel social network mining for interesting ‘following’ patterns. Concurrency Comput. Pract. Exp. 28(15), 3994–4012 (2016)
Leung, C.K., Tanbeer, S.K., Cuzzocrea, A., Braun, P., MacKinnon, R.K.: Interactive mining of diverse social entities. Int. J. Knowl. Based Intell. Eng. Syst. 20(2), 97–111 (2016)
Li, Y.: Socially enhanced account benchmarking in application management service (AMS). IJSC (now STSC) 3(1), 1–13 (2015)
MacKinnon, R.K., Leung, C.K.: Stock price prediction in undirected graphs using a structural support vector machine. In: IEEE/WIC/ACM WI-IAT 2015, vol. 1, pp. 548–555 (2015)
Madden, S.: From databases to big data. IEEE Internet Comput. 16(3), 4–6 (2012)
McAuley, J., Leskovec, J.: Discovering social circles in ego networks. ACM TKDD 8(1), article 4 (2014)
Peterson, B., Baumgartner, G., Wang, Q.: A decentralized scheduling framework for many-task scientific computing in a hybrid cloud. STCC 5(1), 1–13 (2017)
Petri, I., Punceva, M., Rana, O.F., Theodorakopoulos, G., Rezgui, Y.: A broker based consumption mechanism for social clouds. IJCC (now STCC) 2(1), 45–57 (2014)
Rahman, Q.M., Fariha, A., Mandal, A., Ahmed, C.F., Leung, C.K.: A sliding window-based algorithm for detecting leaders from social network action streams. In: IEEE/WIC/ACM WI-IAT 2015, vol. 1, pp. 133–136 (2015)
Salah, K.: A queuing model to achieve proper elasticity for cloud cluster jobs. IJCC (now STCC) 1(1), 53–64 (2013)
Singh, S., Liu, Y., Ding, W., Li, Z.: Empirical evaluation of big data analytics using design of experiment: case studies on telecommunication data. STBD 3(2), 1–20 (2016)
Taber, L., Whittaker, S.: Personality depends on the medium: differences in self-perception on Snapchat, Facebook and offline. In: ACM CHI 2018, paper no. 607 (2018)
Wallace, B., Knoefel, F., Goubran, R., Porter, M.M., Smith, A., Marshall, S.: Features that distinguish drivers: big data analytics of naturalistic driving data. STBD 4(1), 20–32 (2017)
Zeng, J., Min, J.: A systematic framework for designing IoT-enabled systems. STIOT 1(1), 23–31 (2017)
Zhang, J., Jin, S., Yu, P.S.: Mutual community detection across multiple partially aligned social networks. STBD 3(2), 47–69 (2016)
Acknowledgment
This project is partially supported by Natural Sciences and Engineering Research Council of Canada (NSERC) and the University of Manitoba.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Hoi, C.S.H., Leung, C.K., Tran, K., Cuzzocrea, A., Bochicchio, M., Simonetti, M. (2018). Supporting Social Information Discovery from Big Uncertain Social Key-Value Data via Graph-Like Metaphors. In: Xiao, J., Mao, ZH., Suzumura, T., Zhang, LJ. (eds) Cognitive Computing – ICCC 2018. ICCC 2018. Lecture Notes in Computer Science(), vol 10971. Springer, Cham. https://doi.org/10.1007/978-3-319-94307-7_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-94307-7_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-94306-0
Online ISBN: 978-3-319-94307-7
eBook Packages: Computer ScienceComputer Science (R0)