References
- Alexandrov, A., Bergmann, R., Ewen, S., Freytag, J. C., Hueske, F., Heise, … Warneke, D. (2014). The Stratosphere platform for big data analytics. The VLDB Journal – The International Journal on Very Large Data Bases, 23(6), 939–964.
- Álvarez-Moreno, M., De Graaf, C., Lopez, N., Maseras, F., Poblet, J. M., & Bo, C. (2014). Managing the computational chemistry big data problem: The ioChem-BD platform. Journal of Chemical Information and Modeling, 55(1), 95–103.
- Andreu Perez, J., Poon, C., Merrifield, R., Wong, S., & Yang, G. Z. (2015). Big data for health. IEEE Journal of Biomedical and Health Informatics, 19(4), 1193–1208.
- Atayero, A. A., & Feyisetan, O. (2011). Security issues in cloud computing: The potentials of homomorphic encryption. Journal of Emerging Trends in Computing and Information Sciences, 2(10), 546–552.
- Atun, R., Lussier, Y., Poon, C., Wong, S. T. C., & Yang, G. Z. (2015). Editorial: Big data for health. IEEE Journal of Biomedical and Health Informatics, 19(4), 1191–1192.
- Bantouna, A., Poulios, G., Tsagkaris, K., & Demestichas, P. (2014). Network load predictions based on big data and the utilization of self-organizing maps. Journal of Network and Systems Management, 22(2), 150–173.
- Barroso, L. A., Dean, J., & Holzle, U. (2003). Web search for a planet: The Google cluster architecture. IEEE Micro, 23(2), 22–28.
- Bellatreche, L., Cuzzocrea, A., & Song, I. Y. (2015). Advances in data warehousing and OLAP in the big data era. Information Systems, 53(C), 39–40.
- Bendler, J., Wagner, S., Brandt, D. V. T., & Neumann, D. (2014). Taming uncertainty in big data. Business & Information Systems Engineering, 6(5), 279–288.
- Bhimani, A. (2015). Exploring big data's strategic consequences. Journal of Information Technology, 30(1), 66–69.
- Bi, Z., & Cochran, D. (2014). Big data analytics with applications. Journal of Management Analytics, 1(4), 249–265.
- Biem, A., Feng, H., Riabov, A. V., & Turaga, D. S. (2013). Real-time analysis and management of big time-series data. IBM Journal of Research and Development, 57(3/4), 8-1–8-12.
- Bizer, C., Boncz, P., Brodie, M. L., & Erling, O. (2012). The meaningful use of big data: Four perspectives – four challenges. ACM SIGMOD Record, 40(4), 56–60.
- Bourne, P. E. (2014). What big data means to me. Journal of the American Medical Informatics Association, 21(2), 194–194.
- Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication & Society, 15(5), 662–679.
- Bruns, A., & Liang, Y. E. (2012). Tools and methods for capturing Twitter data during natural disasters. First Monday, 17(4), DOI:http://dx.doi.org/10.5210/fm.v17i4.3937.
- Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. New York: W.W. Norton.
- Buhl, H. U. (2013). Interview with Martin Petry on ‘big data’. Business & Information Systems Engineering, 5(2), 101–102.
- Buhl, H. U., Röglinger, M., Moser, D. K. F., & Heidemann, J. (2013). Big data. Business & Information Systems Engineering, 5(2), 65–69.
- Cao, H., Dong, W. S., Liu, L. S., Ma, C. Y., Qian, W. H., Shi, J. W., … Kumar, M. (2014). SoLoMo analytics for telco big data monetization. IBM Journal of Research and Development, 58(5/6), 9–1.
- Cardenas, A. A., Manadhata, P. K., & Rajan, S. P. (2013). Big data analytics for security. IEEE Security & Privacy, (6), 74–76.
- Chandola, V., Banerjee, A., & Kumar, V. (2009). Anomaly detection: A survey. ACM Computing Surveys (CSUR), 41(3), 15.
- Chang, R. M., Kauffman, R. J., & Kwon, Y. (2014). Understanding the paradigm shift to computational social science in the presence of big data. Decision Support Systems, 63, 67–80.
- Chen, C. P., & Zhang, C. Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on big data. Information Sciences, 275(2014), 314–347.
- Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165–1188.
- Chen, J., Chen, Y., Du, X., Li, C., Lu, J., Zhao, S., & Zhou, X. (2013). Big data challenge: A data management perspective. Frontiers of Computer Science, 7(2), 157–164.
- Chen, J., Liang, Q., & Wang, J. (2013). Secure transmission for big data based on nested sampling and coprime sampling with spectrum efficiency. Security and Communication Networks, 8(14), 2447–2456.
- Chen, M., Mao, S., & Liu, Y. (2014). Big data: A survey. Mobile Networks and Applications, 19(2), 171–209.
- Chen, S. C., Jain, R., Tian, Y., & Wang, H. (2015). Guest editorial multimedia: The biggest big data. IEEE Transactions on Multimedia, 17(9), 1401–1403.
- Chen, Y., Li, F., & Fan, J. (2015). Mining association rules in big data with NGEP. Cluster Computing, 18(2), 577–585.
- Chen, Z., Lu, Y., Xiao, N., & Liu, F. (2014). A hybrid memory built by SSD and DRAM to support in-memory big data analytics. Knowledge and Information Systems, 41(2), 335–354.
- Cheng, X., Sun, Y., Jara, A., Song, H., & Tian, Y. (2015). Big data and knowledge extraction for cyber-physical systems. International Journal of Distributed Sensor Networks, 501, 231527.
- Cheung, M., She, J., & Jie, Z. (2015). Connection discovery using big data of user-shared images in social media. IEEE Transactions on Multimedia, 17(9), 1417–1428.
- Chi, C. H., Ding, C., & Liu, Q. (2014). Guest editorial: Knowledge management and big data analytics. Journal of Information Technology, 15(6), 937–938.
- Chong, D., & Shi, H. (2015). Big data analytics: a literature review. Journal of Management Analytics, 2(3), 175–201.
- Constantiou, I. D., & Kallinikos, J. (2015). New games, new rules: Big data and the changing context of strategy. Journal of Information Technology, 30(1), 44–57.
- Debortoli, S., Müller, O., & vom Brocke, J. (2014). Comparing business intelligence and big data skills. Business & Information Systems Engineering, 6(5), 289–300.
- del Río, S., López, V., Benítez, J. M., & Herrera, F. (2014). On the use of MapReduce for imbalanced big data using Random Forest. Information Sciences, 285, 112–137.
- Demirkan, H., & Delen, D. (2013). Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud. Decision Support Systems, 55(1), 412–421.
- Deng, Z., Hu, Y., Zhu, M., Huang, X., & Du, B. (2015). A scalable and fast OPTICS for clustering trajectory big data. Cluster Computing, 18(2), 549–562.
- Dhar, V., Jarke, M., & Laartz, J. (2014). Big data. Business & Information Systems Engineering, 6(5), 257–259.
- Dolin, R. H., Rogers, B., & Jaffe, C. (2015). Health level seven interoperability strategy: Big data, incrementally structured. Methods of Information in Medicine, 54(1), 75–82.
- Duan, L., & Xiong, Y. (2015). Big data analytics and business analytics. Journal of Management Analytics, 2(1), 1–21.
- Earley, S. (2014a). Big data and predictive analytics: What's new? IT Professional, 16(1), 13–15.
- Earley, S. (2014b). Agile analytics in the age of big data. IT Professional, 16(4), 18–20.
- Eckhoff, D., & Sommer, C. (2014). Driving for big data? Privacy concerns in vehicular networking. IEEE Security & Privacy, 1, 77–79.
- Ekbia, H., Mattioli, M., Kouper, I., Arave, G., Ghazinejad, A., Bowman, T., … Sugimoto, C. R. (2015). Big data, bigger dilemmas: A critical review. Journal of the Association for Information Science and Technology, 66(8), 1523–1545.
- Ekins, S., Freundlich, J. S., & Reynolds, R. C. (2014). Are bigger data sets better for machine learning? Fusing single-point and dual-event dose response data for mycobacterium tuberculosis. Journal of Chemical Information and Modeling, 54(7), 2157–2165.
- Ellis, J., Fokoue, A., Hassanzadeh, O., Kementsietsidis, A., Srinivas, K., & Ward, M. J. (2015). Exploring big data with Helix: Finding needles in a big haystack. ACM SIGMOD Record, 43(4), 43–54.
- Frické, M. (2015). Big data and its epistemology. Journal of the Association for Information Science and Technology, 66(4), 651–661.
- Gaspar, H. A., Baskin, I. I., Marcou, G., Horvath, D., & Varnek, A. (2014). Chemical data visualization and analysis with incremental generative topographic mapping: Big data challenge. Journal of Chemical Information and Modeling, 55(1), 84–94.
- Gattiker, A., Gebara, F. H., Hofstee, H. P., Hayes, J. D., & Hylick, A. (2013). Big data text-oriented benchmark creation for Hadoop. IBM Journal of Research and Development, 57(3/4), 10-1–10-6.
- Gelenbe, E., & Abdelrahman, O. (2014). Search in the universe of big networks and data. IEEE Network, 28(4), 20–25.
- Goes, P. B. (2014). Big data and IS research. MIS Quarterly, 38(3), iii–viii.
- Guerard, J. B., Rachev, S. T., & Shao, B. P. (2013). Efficient global portfolios: Big data and investment universes. IBM Journal of Research and Development, 57(5), 11-1–11-11.
- Gurrin, C., Smeaton, A. F., & Doherty, A. R. (2014). Lifelogging: Personal big data. Foundations and Trends in Information Retrieval, 8(1), 1–125.
- Ha, I., Back, B., & Ahn, B. (2015). MapReduce functions to analyze sentiment information from social big data. International Journal of Distributed Sensor Networks, 2015, 1–11.
- Han, Q., Liang, S., & Zhang, H. (2015). Mobile cloud sensing, big data, and 5G networks make an intelligent and smart world. IEEE Network, 29(2), 40–45.
- Han, X., Li, J., Yang, D., & Wang, J. (2013). Efficient skyline computation on big data. IEEE Transactions on Knowledge and Data Engineering, 25(11), 2521–2535.
- Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., & Khan, S. U. (2015). The rise of ‘big data’ on cloud computing: Review and open research issues. Information Systems, 47, 98–115.
- Hirsch, B., & Ng, J. W. (2011). Education beyond the Cloud: Anytime-anywhere learning in a smart campus environment. In IEEE 2011 international conference for internet technology and secured transactions (ICITST), (pp. 718–723).
- Hirzel, M., Andrade, H., Gedik, B., Jacques-Silva, G., Khandekar, R., Kumar, V., … Wu, K. L. (2013). IBM streams processing language: Analyzing big data in motion. IBM Journal of Research and Development, 57(3/4), 7-1–7-11.
- Hitzler, P., & Janowicz, K. (2013). Linked data, Big data, and the 4th paradigm. Semantic Web, 4(3), 233–235.
- Hofstee, H. P., Chen, G. C., Gebara, F. H., Hall, K., Herring, J., Jamsek, D., … Wong, P. W. Y. (2013). Understanding system design for big data workloads. IBM Journal of Research and Development, 57(3/4), 3-1–3-10.
- Hota, C., Upadhyaya, S., & Al-Karaki, J. N. (2015). Advances in secure knowledge management in the big data era. Information Systems Frontiers, 17(5), 983–986.
- Hou, S., Huang, X., Liu, J. K., Li, J., & Xu, L. (2015). Universal designated verifier transitive signatures for graph-based big data. Information Sciences, 318, 144–156.
- IBM. (2013). The four V's of big data [online]. Retrieved from http://dashburst.com/infographic/big-data-volume-varietyvelocity.
- Imran, A., & Zoha, A. (2014). Challenges in 5G: How to empower SON with big data for enabling 5G. IEEE Network, 28(6), 27–33.
- Isakowitz, T., Bieber, M., & Vitali, F. (1998). Web information systems. Communications of the ACM, 41(7), 78–80.
- Jain, R. (2013). Networking for big data. In IEEE CS Keynote at 19th annual international conference on advanced computing and communications (ADCOM).
- Jain, R., Sarkar, P., & Subhraveti, D. (2013). GPFS-SNC: An enterprise cluster file system for big data. IBM Journal of Research and Development, 57(3/4), 5:1–5:10.
- Jardak, C., Mähönen, P., & Riihijärvi, J. (2014). Spatial big data and wireless networks: Experiences, applications, and research challenges. IEEE Network, 28(4), 26–31.
- Jarke, M. (2014a). Interview with Michael Feindt on ‘prescriptive big data analytics’. Business & Information Systems Engineering, 6(5), 301–302.
- Jarke, M. (2014b). Interview with Stefan Wrobel on ‘applied big data research’. Business & Information Systems Engineering, 6(5), 303–304.
- Jeong, S. R., & Ghani, I. (2014). Semantic computing for big data. KSII Transactions on Internet and Information Systems (TIIS), 8(6), 2022–2042.
- Jeong, Y. S., Shyu, M. L., Xu, G., & Wagner, R. R. (2015). Guest editorial: Advanced technologies and services for multimedia big data processing. Multimedia Tools and Applications, 74(10), 3413–3418.
- Jiang, H., Chen, Y., Qiao, Z., Weng, T. H., & Li, K. C. (2015). Scaling up MapReduce-based big data processing on multi-GPU systems. Cluster Computing, 18(1), 369–383.
- Jin, S., Lin, W., Yin, H., Yang, S., Li, A., & Deng, B. (2015). Community structure mining in big data social media networks with MapReduce. Cluster Computing, 18, 999–1010.
- Jo, H. J., & Yoon, J. W. (2015). A new countermeasure against brute-force attacks that use high performance computers for big data analysis. International Journal of Distributed Sensor Networks, 2015, 1–7.
- Joseph, R. C., & Johnson, N. (2013). Big data and transformational government. IT Professional, 15(6), 43–48.
- Ju, H., Hong, C. S., Takano, M., Yoo, J. H., Chang, K. Y., Yoshihara, K., & Jeng, J. Y. (2013). Management in the big data & IoT era: A report on APNOMS 2012. Journal of Network and Systems Management, 21(3), 517–524.
- Jukić, N., Sharma, A., Nestorov, S., & Jukić, B. (2015). Augmenting data warehouses with big data. Information Systems Management, 32(3), 200–209.
- Jung, J. J. (2015a). Special issue editorial: Advances on scalable information systems for big data (InfoScale 2014). Mobile Networks and Applications, 20(4), 1–2.
- Jung, J. J. (2015b). Big bibliographic data analytics by Random Walk Model. Mobile Networks and Applications, 20(4), 533–537.
- Kallinikos, J., & Constantiou, I. D. (2015). Big data revisited: A rejoinder. Journal of Information Technology, 30(1), 70–74.
- Kemelor, P. (2015). Digital data grows into big data. IT Professional, 17(4), 42–48.
- Kim, K. Y. (2014). Business intelligence and marketing insights in an era of big data: The Q-sorting approach. KSII Transactions on Internet and Information Systems (TIIS), 8(2), 567–582.
- Kim, M. K., La, H. J., & Kim, S. D. (2014). A software framework for efficient IoT contexts acquisition and big data analytics. Journal of Internet Technology, 15(6), 939–947.
- Kołodziej, J., Burczyński, T., & Zomaya, A. Y. (2015). A note on energy efficient data, services and memory management in big data information systems. Information Sciences: An International Journal, 319(C), 69–70.
- Kos, A., Tomažič, S., Salom, J., Trifunovic, N., Valero, M., & Milutinovic, V. (2015). New benchmarking methodology and programming model for big data processing. International Journal of Distributed Sensor Networks, 2015, 1–7.
- Kowalczyk, D. W. I. M., & Buxmann, P. (2014). Big data and information processing in organizational decision processes. Business & Information Systems Engineering, 6(5), 267–278.
- Krishnamurthy, P., & Zadorozhny, V. I. (2015). Special section on collaborative big data. Information Systems, 48, 131.
- Lafuente, G. (2015). The big data security challenge. Network Security, 2015(1), 12–14.
- Laney, D. (2001). 3D data management: Controlling data volume, velocity and variety. META Group Research Note, 6, 70.
- Laplante, P. A. (2013). Who's afraid of big data? IT Professional, 15(5), 6–7.
- Laurila, J. K., Gatica-Perez, D., Aad, I., Blom, J., Bornet, O., Do, T. M. T., … Miettinen, M. (2013). From big smartphone data to worldwide research: The mobile data challenge. Pervasive and Mobile Computing, 9(6), 752–771.
- Lee, C. H., & Chien, T. F. (2013). Leveraging microblogging big data with a modified density-based clustering approach for event awareness and topic ranking. Journal of Information Science, 39(4), 523–543.
- Lee, J., Ardakani, H. D., Yang, S., & Bagheri, B. (2015). Industrial big data analytics and cyber-physical systems for future maintenance & service innovation. Procedia CIRP, 38, 3–7.
- Lee, T., Lee, H., Rhee, K. H., & Shin, U. S. (2014). The efficient implementation of distributed indexing with Hadoop for digital investigations on Big Data. Computer Science and Information Systems, 11(3), 1037–1054.
- Lenzerini, M. (2002). Data integration: A theoretical perspective. In Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on principles of database systems (pp. 233–246). ACM, New York, NY, USA. DOI:http://dx.doi.org/10.1145/543613.543644.
- Lesk, M. (2013). Big data, big brother, big money. IEEE Security & Privacy, 4, 85–89.
- Li, B., & Liao, X. (2013). Peer-to-peer in big data management. Peer-to-Peer Networking and Applications, 6(4), 361–362.
- Li, F., & Nath, S. (2014). Scalable data summarization on big data. Distributed and Parallel Databases, 32(3), 313–314.
- Li, X., Tian, Y., Smarandache, F., & Alex, R. (2015). An extension collaborative innovation model in the context of big data. International Journal of Information Technology & Decision Making, 14(01), 69–91.
- Liakos, P., Koltsida, P., Kakaletris, G., Baumann, P., Ioannidis, Y., & Delis, A. (2015). A distributed infrastructure for earth-science big data retrieval. International Journal of Cooperative Information Systems, 24(02), 1550002.
- Liang, Q., Ren, J., Liang, J., Zhang, B., Pi, Y., & Zhao, C. (2015). Security in big data. Security and Communication Networks, 8(14), 2383–2385.
- Lillo-Castellano, J. M., Mora-Jimenez, I., Santiago-Mozos, R., Chavarria-Asso, F., Cano-Gonzalez, A., Garcia-Alberola, A., & Rojo-Alvarez, J. (2015). Symmetrical compression distance for arrhythmia discrimination in cloud-based big data services. IEEE Journal of Biomedical and Health Informatics, 19(4), 1253–1263.
- Liu, C. H. (2015). The study of using big data to solve medical volunteer problem. Journal of Internet Technology, 16(3), 415–430.
- Liu, J., Liu, F., & Ansari, N. (2014). Monitoring and analyzing big traffic data of a large-scale cellular network with Hadoop. IEEE Network, 28(4), 32–39.
- Liu, L. (2013). Computing infrastructure for big data processing. Frontiers of Computer Science, 7(2), 165–170.
- Liu, L., Zhao, S., Yu, Z., & Dai, H. (2015). A big data inspired chaotic solution for fuzzy feedback linearization model in cyber-physical systems. Ad Hoc Networks, 35, 97–104.
- Liu, X., Xu, Y., Li, S., Wang, Y., Peng, J., Luo, C., … Jiang, H. (2014). In silico target fishing: addressing a ‘big data’ problem by ligand-based similarity rankings with data fusion. Journal of Cheminformatics, 6(1), 33.
- Loebbecke, C., & Picot, A. (2015). Reflections on societal and business model transformation arising from digitization and big data analytics: A research agenda. The Journal of Strategic Information Systems, 24(3), 149–157.
- Lu, J., & Li, D. (2013). Bias correction in a small sample from big data. IEEE Transactions on Knowledge and Data Engineering, 25(11), 2658–2663.
- Lu, R., Zhu, H., Liu, X., Liu, J. K., & Shao, J. (2014). Toward efficient and privacy-preserving computing in big data era. IEEE Network, 28(4), 46–50.
- Lycett, M. (2013). ‘Datafication': Making sense of (big) data in a complex world. European Journal of Information Systems, 22(4), 381–386.
- Ma, Y., Wang, L., Liu, P., & Ranjan, R. (2014). Towards building a data-intensive index for big data computing – A case study of remote sensing data processing. Information Sciences, 319, 171–188.
- Malik, P. (2013). Governing big data: Principles and practices. IBM Journal of Research and Development, 57(3/4), 1:1–1:13.
- Margolis, R., Derr, L., Dunn, M., Huerta, M., Larkin, J., Sheehan, J., … Green, E. D. (2014). The National Institutes of Health's Big Data to Knowledge (BD2 K) initiative: Capitalizing on biomedical big data. Journal of the American Medical Informatics Association, 21(6), 957–958.
- Markus, M. L. (2015). New games, new rules, new scoreboards: The potential consequences of big data. Journal of Information Technology, 30(1), 58–59.
- Mayer-Schönberger, V., & Cukier, K. (2013). Big data: A revolution that will transform how we live, work, and think. New York: Houghton Mifflin Harcourt Publishing Company.
- Meaney, P. J., Curley, L. D., Gilda, G. D., Hodges, M. R., Buerkle, D. J., Siegl, R. D., & Dong, R. K. (2015). The IBM z13 memory subsystem for big data. IBM Journal of Research and Development, 59(4/5), 4-1–4-11.
- Mell, P., & Grance, T. (2011). The NIST definition of cloud computing [online]. National Institute of Standards and Technology. Retrieved from http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf?subject=Definition%20of%20Cloud%20Computing
- Mendel, J. M., & Korjani, M. M. (2014). On establishing nonlinear combinations of variables from small to big data for use in later processing. Information Sciences, 280, 98–110.
- Miller, H. G., & Mork, P. (2013). From data to decisions: A value chain for big data. IT Professional, 15(1), 57–59.
- Miller, K., & Morreale, P. (2014). Finding the needle in the image stack: Performance metrics for big data image analysis. IEEE MultiMedia, 21(1), 84–89.
- Mithas, S., Lee, M. R., Earley, S., Murugesan, S., & Djavanshir, R. (2013). Leveraging big data and business analytics [Guest editors’ introduction]. IT Professional, 15(6), 18–20.
- Mohammed, J. (2014). Evolution of the next generation of technologies: Mobile and ubiquitous computing. Evolution, 1(5), 247–253.
- Nara, A. (2015). Book review of Big data: Techniques and technologies in geoinformatics, edited by Hassan A. Karimi. International Journal of Geographical Information Science, 29(4), 694–696.
- National Research Council (2013). Frontiers in massive data analysis. Washington, DC: The National Academies Press.
- Nguyen, H. T. H., & Cao, J. (2014). Trustworthy answers for top-k queries on uncertain big data in decision making. Information Sciences, 318, 73–90.
- Obrst, L., Gruninger, M., Baclawski, K., Bennett, M., Brickley, D., Berg-Cross, G., … Yim, P. (2014). Semantic web and big data meets applied ontology: The Ontology Summit 2014. Applied Ontology, 9(2), 155–170.
- Ohno-Machado, L. (2012). Big science, big data, and a big role for biomedical informatics. Journal of the American Medical Informatics Association, 19(e1), e1.
- Ohno-Machado, L. (2014). NIH's Big Data to Knowledge initiative and the advancement of biomedical informatics. Journal of the American Medical Informatics Association, 21(2), 193–193.
- O'Sullivan, P., Thompson, G., & Clifford, A. (2014). Applying data models to big data architectures. IBM Journal of Research and Development, 58(5/6), 18-1–18-11.
- Oztekin, A. (2011). A decision support system for usability evaluation of web-based information systems. Expert Systems with Applications, 38(3), 2110–2118.
- Paquette, S., Jaeger, P., & Wilson, S. (2010). Identifying the security risks associated with governmental user of cloud computing. Government Information Quarterly, 27, 245–253.
- Paredes-Oliva, I., Barlet-Ros, P., & Dimitropoulos, X. (2013). FaRNet: Fast recognition of high-dimensional patterns from big network traffic data. Computer Networks, 57(18), 3897–3913.
- Park, H. W., Yeo, I. Y., Lee, J. R., & Jang, H. (2014). Study on network architecture of big data center for the efficient control of huge data traffic. Computer Science and Information Systems, 11(3), 1113–1126.
- Park, J. H., Hung, J. C., Yen, N. Y., & Jeong, Y. S. (2014). Advanced convergence technologies: big data, IoT, cloud computing. Journal of Internet Technology, 15(4), 589–591.
- Pei, S., Chen, G., Zhang, S., Wu, B., & Xiong, N. (2014). Inter-block multi-erasure coding scheme for cloud-based big bulk data transmission. Journal of Internet Technology, 15(6), 1013–1023.
- Peng, Z., Liao, J., & Cai, Y. (2015). Differential evolution with distributed direction information based mutation operators: An optimization technique for big data. Journal of Ambient Intelligence and Humanized Computing, 6, 481–494.
- Perera, C., Ranjan, R., Wang, L., Khan, S. U., & Zomaya, A. Y. (2015). Big data privacy in the Internet of Things era. IT Professional, 17(3), 32–39.
- Perera, C., Zaslavsky, A., Christen, P., & Georgakopoulos, D. (2014). Sensing as a service model for smart cities supported by Internet of Things. Transactions on Emerging Telecommunications Technologies, 25(1), 81–93.
- Qin, W., Zhang, J., Li, B., & Sun, L. (2013). Discovering human presence activities with smartphones using nonintrusive wi-fi sniffer sensors: The big data prospective. International Journal of Distributed Sensor Networks, 2013, 1–12.
- Qu, X., Latino, D. A., & Aires-de-Sousa, J. (2013). A big data approach to the ultra-fast prediction of DFT-calculated bond energies. Journal of Cheminformatics, 5(34), 1–13.
- Rakthanmanon, T., Campana, B., Mueen, A., Batista, G., Westover, B., Zhu, Q., … Keogh, E. (2013). Addressing big data time series: Mining trillions of time series subsequences under dynamic time warping. ACM Transactions on Knowledge Discovery from Data (TKDD), 7(3), 10.
- Ram, S., Zhang, W., Williams, M., & Pengetnze, Y. (2015). Predicting asthma-related emergency department visits using big data. IEEE Journal of Biomedical and Health Informatics, 19(4), 1216–1223.
- Rao, P., Kwon, J., Lee, S., & Subramaniam, L. V. (2015). Advanced big data management and analytics for ubiquitous sensors. International Journal of Distributed Sensor Networks, 2015, 1.
- Ratha, N. K., Connell, J. H., & Pankanti, S. (2015). Big data approach to biometric-based identity analytics. IBM Journal of Research and Development, 59(2/3), 4-1–4-11.
- Romero, O., Herrero, V., Abelló, A., & Ferrarons, J. (2015). Tuning small analytics on big data: Data partitioning and secondary indexes in the Hadoop ecosystem. Information Systems, 54, 336–356.
- Russom, P. (2011). Big data analytics. TDWI Best Practices Report, Fourth Quarter, the Data Warehousing Institute, Renton, WA.
- Sahoo, S. S., Jayapandian, C., Garg, G., Kaffashi, F., Chung, S., Bozorgi, A., … Zhang, G. Q. (2014). Heart beats in the cloud: Distributed analysis of electrophysiological ‘big data’ using cloud computing for epilepsy clinical research. Journal of the American Medical Informatics Association, 21(2), 263–271.
- Saleem, M., Kamdar, M. R., Iqbal, A., Sampath, S., Deus, H. F., & Ngomo, A. C. N. (2014). Big linked cancer data: Integrating linked TCGA and PubMed. Web Semantics: Science, Services and Agents on the World Wide Web, 27, 34–41.
- Samuel, A., Sarfraz, M. I., Haseeb, H., Basalamah, S., & Ghafoor, A. (2015). A framework for composition and enforcement of privacy-aware and context-driven authorization mechanism for multimedia big data. IEEE Transactions on Multimedia, 17(9), 1484–1494.
- Sandhu, R., & Sood, S. K. (2015). Scheduling of big data applications on distributed cloud based on QoS parameters. Cluster Computing, 18(2), 817–828.
- Schroeck, M., Shockley, R., Smart, J., Romero-Morales, D., & Tufano, P. (2012). Analytics: The real-world use of big data. Somers: IBM Global Business Services.
- Sfrent, A., & Pop, F. (2015). Asymptotic scheduling for many task computing in big data platforms. Information Sciences, 319, 71–91.
- Shah, T., Rabhi, F., & Ray, P. (2014). Investigating an ontology-based approach for big data analysis of inter-dependent medical and oral health conditions. Cluster Computing, 18(1), 351–367.
- Shen, Y., & Zhang, Y. (2014). Transmission protocol for secure big data in two-hop wireless networks with cooperative jamming. Information Sciences, 281(2014), 201–210.
- Singh, K., Guntuku, S. C., Thakur, A., & Hota, C. (2014). Big data analytics framework for peer-to-peer botnet detection using random forests. Information Sciences, 278, 488–497.
- Song, G. Y., Cheon, Y., Park, K. M., & Rim, H. C. (2014). Inter-category map: Building cognition network of general customers through big data mining. KSII Transactions on Internet and Information Systems (TIIS), 8(2), 583–600.
- Spiess, J., T'Joens, Y., Dragnea, R., Spencer, P., & Philippart, L. (2014). Using big data to improve customer experience and business performance. Bell Labs Technical Journal, 18(4), 3–17.
- Srinivasan, U., & Arunasalam, B. (2013). Leveraging big data analytics to reduce healthcare costs. IT Professional, 15(6), 21–28.
- Staff, W. (2012). Virtualization overview [online]. White Paper. Retrieved from http://www.vmware.com/pdf/virtualization.pdf
- Stonebraker, M., Madden, S., & Dubey, P. (2013). Intel big data science and technology center vision and execution plan. ACM SIGMOD Record, 42(1), 44–49.
- Stuart, D. (2015). The data revolution: Big data, open data, data infrastructures and their consequences. Online Information Review, 39(2), 272.
- Suinesiaputra, A., Cowan, B., Medrano-Gracia, P., & Young, A. (2014). Big heart data: Advancing health informatics through data sharing in cardiovascular imaging. IEEE Journal of Biomedical and Health Informatics, 19(4), 1283–1290.
- Sun, D., Chang, G., Sun, L., & Wang, X. (2011). Surveying and analyzing security, privacy and trust issues in cloud computing environments. Procedia Engineering, 15, 2852–2856.
- Sun, D., Zhang, G., Yang, S., Zheng, W., Khan, S. U., & Li, K. (2015). Re-Stream: Real-time and energy-efficient resource scheduling in big data stream computing environments. Information Sciences, 319, 92–112.
- Sun, N., Morris, J. G., Xu, J., Zhu, X., & Xie, M. (2014). iCARE: A framework for big data-based banking customer analytics. IBM Journal of Research and Development, 58(5/6), 4-1–4-9.
- Sun, S., Gong, J., He, J., & Peng, S. (2015). A spreading activation algorithm of spatial big data retrieval based on the spatial ontology model. Cluster Computing, 18(2), 563–575.
- Sun, Y., Yan, H., Zhang, J., Xia, Y., Wang, S., Bie, R., & Tian, Y. (2014). Organizing and querying the big sensing data with event-linked network in the Internet of Things. International Journal of Distributed Sensor Networks, 2014, 1–11.
- Sung, Y., Jeong, H. Y., Cho, K., & Um, K. (2014). Robot service framework based on big data technology. Journal of Internet Technology, 15(4), 593–603.
- Tang, H., Yang, X., & Zhang, Y. (2014). Effort at constructing big data sensor networks for monitoring greenhouse gas emission. International Journal of Distributed Sensor Networks, 2014, 1–7.
- Tang, L. A., Yu, X., Gu, Q., Han, J., Jiang, G., Leung, A., & Porta, T. L. (2015). A framework of mining trajectories from untrustworthy data in cyber-physical system. ACM Transactions on Knowledge Discovery from Data (TKDD), 9(3), 16.
- Tian, Y., Chen, S. C., Shyu, M. L., Huang, T., Sheu, P., & Del Bimbo, A. (2015). Multimedia big data. IEEE MultiMedia, 3, 93–95.
- Ting, K. M., Washio, T., Wells, J. R., Liu, F. T., & Aryal, S. (2013). DEMass: A new density estimator for big data. Knowledge and Information Systems, 35(3), 493–524.
- Um, J. H., Jeong, C. H., Choi, S. P., Lee, S., Kim, H. M., & Jung, H. (2013). Distributed and parallel big textual data parsing for social sensor network. International Journal of Distributed Sensor Networks, 2013, 1–6.
- Vera-Baquero, A., Colomo-Palacios, R., & Molloy, O. (2013). Business process analytics using a big data approach. IT Professional, 15(6), 29–35.
- Viceconti, M., Hunter, P., & Hose, D. (2015). Big data, big knowledge: Big data for personalised healthcare. IEEE Journal of Biomedical and Health Informatics, 19(4), 1209–1215.
- Wang, H., Jiang, X., & Kambourakis, G. (2015). Special issue on security, privacy and trust in network-based big data. Information Sciences: An International Journal, 318(C), 48–50.
- Wang, H., Qin, X., Zhou, X., Li, F., Qin, Z., Zhu, Q., & Wang, S. (2015). Efficient query processing framework for big data warehouse: An almost join-free approach. Frontiers of Computer Science, 9(2), 224–236.
- Wang, W., Zhou, X., Zhang, B., & Mu, J. (2013). Anomaly detection in big data from UWB radars. Security and Communication Networks, 8, 2469–2475.
- Wang, Y., Liu, Z., Liao, H., & Li, C. (2015). Improving the performance of GIS polygon overlay computation with MapReduce for spatial big data processing. Cluster Computing, 18(2), 507–516.
- Wei, G., Shao, J., Xiang, Y., Zhu, P., & Lu, R. (2014). Obtain confidentiality or/and authenticity in big data by ID-based generalized signcryption. Information Sciences, 318, 111–122.
- Woerner, S., & Wixom, B. H. (2015). Big data: Extending the business strategy toolbox. Journal of Information Technology, 30(1), 60–62.
- Wu, X., Zhu, X., Wu, G. Q., & Ding, W. (2014). Data mining with big data. IEEE Transactions on Knowledge and Data Engineering, 26(1), 97–107.
- Wyld, D. (2009). Moving to the cloud: An introduction to cloud computing in government. E-Government Series. IBM Center for the Business of Government, Washington, DC.
- Xiao, F., Zhang, C., & Han, Z. (2014). Big data in ubiquitous wireless sensor networks. International Journal of Distributed Sensor Networks, 2014, 1–2.
- Xiao, J., Liao, L., Hu, J., Chen, Y., & Hu, R. (2015). Exploiting global redundancy in big surveillance video data for efficient coding. Cluster Computing, 18(2), 531–540.
- Xing, W., Jie, W., Tsoumakos, D., & Ghanem, M. (2015). A network approach for managing and processing big cancer data in clouds. Cluster Computing, 18, 1285–1294.
- Xiong, H., Wang, J., Srivastava, J., & Chen, E. (2015). Editor's note: Special section on web information management in the big data era. World Wide Web, 18(3), 707.
- Xu, W. J., Zhao, C. D., Chiang, H. P., Huang, L., & Huang, Y. M. (2015). The RR-PEVQ algorithm research based on active area detection for big data applications. Multimedia Tools and Applications, 74(10), 3507–3520.
- Xu, X., Zhao, J., Xu, G., Ding, Y., & Dong, Y. (2014). DSMC: A novel distributed store-retrieve approach of internet data using MapReduce model and community detection in big data. International Journal of Distributed Sensor Networks, 2014, 1–12.
- Yang, J., Li, X., Wang, D., & Wang, J. (2014). A group mining method for big data on distributed vehicle trajectories in WAN. International Journal of Distributed Sensor Networks, 2015, 1–9.
- Yao, S., Wang, Y., & Niu, B. (2015). An efficient cascaded filtering retrieval method for big audio data. IEEE Transactions on Multimedia, 17(9), 1450–1459.
- Yesudas, M., Menon, G., & Ramamurthy, V. (2014). Intelligent operational dashboards for smarter commerce using big data. IBM Journal of Research and Development, 58(5/6), 13–1.
- Yi, X., Liu, F., Liu, J., & Jin, H. (2014). Building a network highway for big data: Architecture and challenges. IEEE Network, 28(4), 5–13.
- Yin, H., Jiang, Y., Lin, C., Luo, Y., & Liu, Y. (2014). Big data: Transforming the design philosophy of future internet. IEEE Network, 28(4), 14–19.
- Yin, X., & Sun, Y. (2013). Secure and efficient integration of big data for multi-cells based on micro images. Security and Communication Networks, 8(14), 2411–2415.
- Yoo, Y. (2015). It is not about size: A further thought on big data. Journal of Information Technology, 30(1), 63–65.
- Yu, Y., Zhao, J., Wang, X., Wang, Q., & Zhang, Y. (2015). Cludoop: An efficient distributed density-based clustering for big data using Hadoop. International Journal of Distributed Sensor Networks, 2015, 1–13.
- Zezula, P. (2015). Similarity searching for the big data: Challenges and research objectives. Mobile Networks and Applications, 20, 487–496.
- Zhang, H., Chen, G., Ooi, B. C., Tan, K. L., & Zhang, M. (2015). In-memory big data management and processing: A survey. IEEE Transactions on Knowledge and Data Engineering, 27(7), 1920–1948.
- Zhang, J., Li, H., Gao, Q., Wang, H., & Luo, Y. (2014). Detecting anomalies from big network traffic data using an adaptive detection approach. Information Sciences, 318, 91–110.
- Zhang, L. J. (2012). Editorial. Big services era: Global trends of cloud computing and big data. IEEE Transactions on Services Computing, 4, 467–468.
- Zhang, Q., & Chen, Z. (2014). A distributed weighted possibilistic c-means algorithm for clustering incomplete big sensor data. International Journal of Distributed Sensor Networks, 2014, 1–8.
- Zhang, Q., Chen, Z., & Leng, Y. (2015). Distributed fuzzy c-means algorithms for big sensor data based on cloud computing. International Journal of Sensor Networks, 18(1–2), 32–39.
- Zhang, Y., Chen, M., Mao, S., Hu, L., & Leung, V. (2014). Cap: Community activity prediction based on big data analysis. IEEE Network, 28(4), 52–57.
- Zhang, Y., Chen, S., Wang, Q., & Yu, G. (2015). i2MapReduce: Incremental MapReduce for mining evolving big data. IEEE Transactions on Knowledge and Data Engineering, 27(7), 1906–1919.
- Zheng, N., Zhang, J., & Wang, C. (2014). Special issue on big data research in China. Knowledge and Information Systems, 41(2), 247–249.
- Zhou, M., Zhang, R., Xie, W., Qian, W., & Zhou, A. (2010). Security and privacy in cloud computing: A survey. In IEEE Semantics Knowledge and Grid (SKG), 2010 Sixth International Conference on (pp. 105–112).
- Zhou, Q., Xiao, D., Tang, Y., & Rong, C. (2014). Trusted big data capture and transport architecture for wireless sensor network. Journal of Internet Technology, 15(6), 1033–1041.
- Zhu, W., Cui, P., Wang, Z., & Hua, G. (2015). Multimedia big data computing. IEEE MultiMedia, 22(3), 96–105.