Big data reduction framework for value creation in sustainable enterprises

International Journal of Information Management

Volumn 36, Issue 6, 2016, Pages 917-928

  Rehman, Muhammad Habib Ur ^a   Chang, Victor ^b   Batool, Aisha ^c   Wah, Teh Ying ^a  

^a UNIVERSITY OF MALAYA   (Malaysia)

^b XI AN JIAOTONG LIVERPOOL UNIVERSITY   (China)

^c IQRA UNIVERSITY   (Pakistan)

Author keywords

Big data analytics; Business model; Data reduction; Sustainable enterprises; Value creation

Indexed keywords

ADVANCED ANALYTICS; BIG DATA; COMMERCE; DATA ANALYTICS; HUMAN RESOURCE MANAGEMENT; INFORMATION MANAGEMENT; SALES; SUPPLY CHAIN MANAGEMENT; SUSTAINABLE DEVELOPMENT;

BUSINESS MODELING; ENTERPRISE APPLICATIONS; FUTURE APPLICATIONS; MULTIPLE-OBJECTIVES; PROFIT MAXIMIZATION; REDUCTION OPERATION; SUSTAINABLE ENTERPRISE; VALUE CREATION;

DATA REDUCTION;

EID: 84975070005     PISSN: 02684012     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijinfomgt.2016.05.013     Document Type: Article

References (72)

1. K. Ackermann, and S.D. Angus A resource efficient big data analysis method for the social sciences: the case of global IP activity Procedia Computer Science 29 2014 2360 2369
2. C.C. Aggarwal Outlier analysis Paper presented at the data mining 2015
3. F. Akhbar, V. Chang, Y. Yao, and V.M. Muñoz Outlook on moving of computing services towards the data sources International Journal of Information Management 36 4 2016 645 652
4. A. Amini, T.Y. Wah, and H. Saboohi On density-based data streams clustering algorithms: a survey Journal of Computer Science and Technology 29 1 2014 116 141
5. A. Antonic, K. Roankovic, M. Marjanovic, K. Pripuic, and I.P. Zarko A mobile crowdsensing ecosystem enabled by a cloud-based publish/subscribe middleware Paper presented at the future internet of things and cloud (FiCloud), 2014 international conference on 2014
6. R.C. Barros, M.P. Basgalupp, A.C. De Carvalho, and A. Freitas A survey of evolutionary algorithms for decision-tree induction Systems, man, and cybernetics, part C: applications and reviews, IEEE transactions on 42 3 2012 291 312
7. Brown, C.T. (2012). BIGDATA: Small: DA: DCM: Low-memory Streaming Prefilters for Biological Sequencing Data. DCM, July de.
8. V. Chang, and G. Wills A model to compare cloud and non-cloud storage of Big Data Future Generation Computer Systems 57 2016 56 76
9. V. Chang, R.J. Walters, and G. Wills The development that leads to the cloud computing business framework International Journal of Information Management 33 3 2013 524 538
10. V. Chang The business intelligence as a service in the cloud Future Generation Computer Systems 37 2014 512 534
11. X.-W. Chen, and X. Lin Big data deep learning: challenges and perspectives IEEE Access 2 2014 514 525
12. S.H. Chen, and C.A. Pollino Good practice in Bayesian network modelling Environmental Modelling & Software 37 2012 134 145
13. Y. Cheng, P. Jiang, and Y. Peng Increasing big data front end processing efficiency via locality sensitive Bloom filter for elderly healthcare Paper presented at the computational intelligence in big data (CIBD), 2014 IEEE symposium on 2014
14. D.C. Chou Cloud computing: a value creation model Computer Standards & Interfaces 38 2015 72 77
15. H.-M. Chuang, and Y.-S. Chen Identifying the value co-creation behavior of virtual customer environments using a hybrid expert-based DANP model in the bicycle industry Human-centric Computing and Information Sciences 5 1 2015 1 31
16. F.-J. Cossío-Silva, M.-Á. Revilla-Camacho, M. Vega-Vázquez, and B. Palacios-Florencio Value co-creation and customer loyalty Journal of Business Research 2015
17. CrowdFlower. (2015). CrowdFlower 2015 Data Scientist Report. Online.
18. B. Di Martino, R. Aversa, G. Cretella, A. Esposito, and J. Kołodziej Big data (lost) in the cloud International Journal of Big Data Intelligence 1 1-2 2014 3 17
19. W. Dong, F. Douglis, K. Li, R.H. Patterson, S. Reddy, and P. Shilane Tradeoffs in scalable data routing for deduplication clusters Paper presented at the FAST 2011
20. N.R. Draper, and H. Smith Applied regression analysis 2014 John Wiley & Sons
21. D. Feldman, M. Schmidt, and C. Sohler Turning big data into tiny data: constant-size coresets for k-means, pca and projective clustering Paper presented at the proceedings of the twenty-Fourth annual ACM-SIAM symposium on discrete algorithms 2013
22. Y. Fu, H. Jiang, and N. Xiao A scalable inline cluster deduplication framework for big data protection Middleware 2012 2012 Springer 354 373
23. A. Gandomi, and M. Haider Beyond the hype: big data concepts, methods, and analytics International Journal of Information Management 35 2 2015 137 144
24. A. Gani, A. Siddiqa, S. Shamshirband, and F. Hanum A survey on indexing techniques for big data: taxonomy and performance evaluation Knowledge and Information Systems 46 2 2016 241 284
25. M. Grzegorowski, and S. Stawicki Window-based feature extraction framework for multi-sensor data: a posture recognition case study Paper presented at the computer science and information systems (FedCSIS), 2015 federated conference on 2015
26. N. Haile, and J. Altmann Value creation in software service platforms Future Generation Computer Systems 55 2016 495 509
27. I.A.T. Hashem, I. Yaqoob, N.B. Anuar, S. Mokhtar, A. Gani, and S.U. Khan The rise of big data on cloud computing: review and open research issues Information Systems 47 2015 98 115
28. C.-J. Hsieh, M.A. Sustik, I.S. Dhillon, P.K. Ravikumar, and R. Poldrack BIG & QUIC: sparse inverse covariance estimation for a million variables Paper presented at the advances in neural information processing systems 2013
29. Insights, C. (2016). The Top 20 Reasons Startups Fail. Online.
30. A.K. Jain Data clustering: 50 years beyond K-means Pattern Recognition Letters 31 8 2010 651 666
31. B. Jalali, and M.H. Asghari The anamorphic stretch transform: putting the squeeze on big data Optics and Photonics News 25 2 2014 24 31
32. Jiang, P.; Winkley, J.; Zhao, C.; Munnoch, R.; Min, G.; & Yang, L.T. (2014). An intelligent information forwarder for healthcare big data systems with distributed wearable sensors.
33. J. Konstan, and J. Riedl Deconstructing recommender systems: how Amazon and Netflix predict your preferences and prod you to purchase IEEE Spectrum 2012 49
34. S. LaValle, E. Lesser, R. Shockley, M.S. Hopkins, and N. Kruschwitz Big data, analytics and the path from insights to value MIT Sloan Management Review 2013 21
35. D. Larson, and V. Chang A review and future direction of agile, business intelligence, analytics and data science International Journal of Information Management 36 5 2016 700 710
36. C.K.-S. Leung, R.K. MacKinnon, and F. Jiang Reducing the search space for big data mining for interesting patterns from uncertain data Paper presented at the big data (BigData congress), 2014 IEEE international congress on 2014
37. C.-S. Li, F. Darema, and V. Chang Distributed behavior model orchestration in cognitive internet of things solution International Journal of Information Management 2016
38. M.-S. Lin, C.-Y. Chiu, Y.-J. Lee, and H.-K. Pao Malicious URL filtering - A big data application Paper presented at the big data, 2013 IEEE international conference on 2013
39. G. Liu, M. Iwai, Y. Tobe, and K. Sezaki REPSense: on-line sensor data reduction while preserving data diversity for mobile sensing Paper presented at the 2013 IEEE 9th international conference on wireless and mobile computing, networking and communications (WiMob) 2013
40. T.H. Luan, L. Gao, Z. Li, Y. Xiang, L. Sun, 2015. Fog computing: focusing on mobile users at the edge arXiv preprint arXiv:1502.01815.
41. M. Mital, V. Chang, P. Choudhary, A. Pani, and Z. Sun Adoption of cloud based Internet of Things in India: a multiple theory perspective International Journal of Information Management 2016
42. M. Moshtaghi, J.C. Bezdek, C. Leckie, S. Karunasekera, and M. Palaniswami Evolving fuzzy rules for anomaly detection in data streams IEEE Transactions on Fuzzy Systems 23 3 2015 688 700
43. A. Osterwalder, Y. Pigneur, and C.L. Tucci Clarifying business models: origins, present, and future of the concept Communications of the Association for Information Systems 16 1 2005 1
44. Z. Pang, Q. Chen, W. Han, and L. Zheng Value-centric design of the internet-of-things solution for food supply chain: value creation, sensor portfolio and information fusion Information Systems Frontiers 17 2 2015 289 319
45. A. Papageorgiou, M. Schmidt, J. Song, and N. Kami Smart m2m data filtering using domain-specific thresholds in domain-agnostic platforms Paper presented at the big data (BigData congress), 2013 IEEE International Congress on 2013
46. N. Patel 90% of startups fail: here's what you need to know about the 10% 2015 (Retrieved 11.05.16) http://www.forbes.com/sites/neilpatel/2015/01/16/90-of-startups-will-fail-heres-what-you-need-to-know-about-the-10/#62c11ac955e1
47. J.W. Patty, and E.M. Penn Analyzing big data: social choice and measurement PS: Political Science & Politics 48 01 2015 95 101
48. J.-Y. Qi, Q.-X. Qu, and Y.-P. Zhou How does customer self-construal moderate CRM value creation chain? Electronic Commerce Research and Applications 13 5 2014 295 304
49. A. Rágyanszki, K.Z. Gerlei, A. Surányi, A. Kelemen, S.J.K. Jensen, I.G. Csizmadia, and B. Viskolcz Big data reduction by fitting mathematical functions: a search for appropriate functions to fit Ramachandran surfaces Chemical Physics Letters 625 2015 91 97
50. M.H. Rehman, and A. Batool The concept of pattern based data sharing in big data environments International Journal of Database Theory and Application 8 4 2015 11 18
51. M.H. Rehman, C.S. Liew, and T.Y. Wah Frequent pattern mining in mobile devices: a feasibility study Paper presented at the information technology and multimedia (ICIMU), 2014 International Conference on 2014
52. M.H. Rehman, A. Khan, and A. Batool Big data analytics in mobile and cloud computing environments Q. Hussain, Handbook of research on next-Generation high performance computing Vol. 1 2016 IGI Global
53. R. Rojas Neural networks: a systematic introduction 2013 Springer Science & Business Media
54. J. Salmon, Z. Harmany, C.-A. Deledalle, and R. Willett Poisson noise reduction with non-local PCA Journal of Mathematical Imaging and Vision 48 2 2014 279 294
55. S. Sharma, V. Chang, U.S. Tim, J. Wong, and S. Gadia Cloud-based emerging services systems International Journal of Information Management 2016
56. N. Singh, A. Javeed, S. Chhabra, and P. Kumar Missing value imputation with unsupervised Kohonen self organizing Map emerging research in computing, information, communication and applications 2015 Springer 61 76
57. A. Stateczny, and M. Wlodarczyk-Sielicka Self-organizing artificial neural networks into hydrographic big data reduction process Rough sets and intelligent systems paradigms 2014 Springer 335 342
58. M. Trovati, and N. Bessis An influence assessment method based on co-occurrence for topologically reduced big data sets Soft Computing 2015 1 10
59. M. Trovati Reduced topologically real-world networks: a big-data approach International Journal of Distributed Systems and Technologies (IJDST) 6 2 2015 13 27
60. A. Vera-Baquero, R. Colomo-Palacios, and O. Molloy Business process analytics using a big data approach IT Professional 15 6 2013 29 35
61. P.C. Verhoef, E. Kooge, and N. Walk Creating value with big data analytics: making smarter marketing decisions 2016 Routledge
62. N. Vervliet, O. Debals, L. Sorber, and L. De Lathauwer Breaking the curse of dimensionality using decompositions of incomplete tensors: tensor-based scientific computing in big data analysis Signal Processing Magazine, IEEE 31 5 2014 71 79
63. Vidgen, R. (2014). Creating business value from Big Data and business analytics: organizational, managerial and human resource implications.
64. Weinstein, M.; Meirer, F.; Hume, A.; Sciau, P.; Shaked, G.; & Hofstetter, R.; et al. (2013). Analyzing big data with dynamic quantum clustering. arXiv preprint arXiv:1310.2700.
65. Wu, C.; Buyya, R.; & Ramamohanarao, K. (2016). Big Data Analytics = Machine Learning + Cloud Computing. arXiv preprint arXiv:1601.03115.
66. W. Xia, H. Jiang, D. Feng, and Y. Hua SiLo: a similarity-Locality based near-Exact deduplication scheme with low RAM overhead and high throughput Paper presented at the USENIX Annual Technical Conference 2011
67. T. Xu, Z. Zhang, P.S. Yu, and B. Long Generative models for evolutionary clustering ACM Transactions on Knowledge Discovery from Data (TKDD) 6 2 2012 7
68. C. Yang, X. Zhang, C. Zhong, C. Liu, J. Pei, K. Ramamohanarao, and et al. A spatiotemporal compression based approach for efficient big data processing on cloud Journal of Computer and System Sciences 80 8 2014 1563 1583
69. I. Yaqoob, V. Chang, A. Gani, S. Mokhtar, I.A.T. Hashem, E. Ahmed, and et al. Information fusion in social big data: foundations, state-of-the-art, applications, challenges, and future research directions International Journal of Information Management 2016
70. Y. Zhai, Y.-S. Ong, and I.W. Tsang The emerging big dimensionality Computational Intelligence Magazine, IEEE 9 3 2014 14 26
71. R. Zhou, M. Liu, and T. Li Characterizing the efficiency of data deduplication for big data storage management Paper presented at the workload characterization (IISWC), 2013 IEEE International Symposium on 2013
72. A. Zolnowski, C. Weiß, and T. Bohmann Representing service business models with the service business model Canvas-the case of a mobile payment service in the retail industry Paper presented at the system sciences (HICSS), 2014 47th Hawaii International Conference on 2014