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Volumn 2, Issue 1, 2015, Pages 1-21

Big data analytics and business analytics

Author keywords

big data analytics; business analytics; business intelligence; management analytics; marketing analytics

Indexed keywords


EID: 84979665325     PISSN: 23270012     EISSN: 23270039     Source Type: Journal    
DOI: 10.1080/23270012.2015.1020891     Document Type: Article
Times cited : (152)

References (142)
  • 1
    • 84868021372 scopus 로고    scopus 로고
    • Metafraud: A meta-learning framework for detecting financial fraud
    • Abbasi, A., Albrecht, C., Vance, A., & Hansen, J., (2012). Metafraud: A meta-learning framework for detecting financial fraud. MIS Quarterly, 36(4), 1293–1327.
    • (2012) MIS Quarterly , vol.36 , Issue.4 , pp. 1293-1327
    • Abbasi, A.1    Albrecht, C.2    Vance, A.3    Hansen, J.4
  • 5
    • 77958488310 scopus 로고    scopus 로고
    • Deep machine learning–A new frontier in artificial intelligence research
    • Arel, I., Rose, D. C., & Karnowski, T. P., (2010). Deep machine learning–A new frontier in artificial intelligence research. Computational Intelligence Magazine, IEEE, 5(4), 13–18.
    • (2010) Computational Intelligence Magazine, IEEE , vol.5 , Issue.4 , pp. 13-18
    • Arel, I.1    Rose, D.C.2    Karnowski, T.P.3
  • 6
    • 43949152639 scopus 로고
    • Genetic algorithm learning and the cobweb model
    • Arifovic, J., (1994). Genetic algorithm learning and the cobweb model. Journal of Economic Dynamics and Control, 18(1), 3–28.
    • (1994) Journal of Economic Dynamics and Control , vol.18 , Issue.1 , pp. 3-28
    • Arifovic, J.1
  • 14
    • 0021583718 scopus 로고
    • FCM: The fuzzy c-means clustering algorithm
    • Bezdek, J. C., Ehrlich, R., & Full, W., (1984). FCM: The fuzzy c-means clustering algorithm. Computers & Geosciences, 10(2), 191–203.
    • (1984) Computers & Geosciences , vol.10 , Issue.2 , pp. 191-203
    • Bezdek, J.C.1    Ehrlich, R.2    Full, W.3
  • 18
  • 24
    • 0001626339 scopus 로고
    • A classification EM algorithm for clustering and two stochastic versions
    • Celeux, G., & Govaert, G., (1992). A classification EM algorithm for clustering and two stochastic versions. Computational Statistics & Data Analysis, 14(3), 315–332.
    • (1992) Computational Statistics & Data Analysis , vol.14 , Issue.3 , pp. 315-332
    • Celeux, G.1    Govaert, G.2
  • 26
    • 85025685678 scopus 로고    scopus 로고
    • Innovations in business forecasting: Predictive analytics
    • Chase, J. C. W., (2014). Innovations in business forecasting: Predictive analytics. Journal of Business Forecasting, 33(2), 26–32.
    • (2014) Journal of Business Forecasting , vol.33 , Issue.2 , pp. 26-32
    • Chase, J.C.W.1
  • 27
    • 84868008189 scopus 로고    scopus 로고
    • Business intelligence in blogs: Understanding consumer interactions and communities
    • Chau, M., & Xu, J., (2012). Business intelligence in blogs: Understanding consumer interactions and communities. MIS Quarterly, 36(4), 1189–1216.
    • (2012) MIS Quarterly , vol.36 , Issue.4 , pp. 1189-1216
    • Chau, M.1    Xu, J.2
  • 28
    • 84952005833 scopus 로고    scopus 로고
    • Mining the past to see the future
    • Cokins, G., (2014). Mining the past to see the future. Strategic Finance, 96(11), 23–30.
    • (2014) Strategic Finance , vol.96 , Issue.11 , pp. 23-30
    • Cokins, G.1
  • 30
    • 0347765758 scopus 로고    scopus 로고
    • Clustering and upscaling of station precipitation records to regional patterns using self-organizing maps (SOMs)
    • Crane, R. G., & Hewitson, B. C., (2003). Clustering and upscaling of station precipitation records to regional patterns using self-organizing maps (SOMs). Climate Research, 25(2), 95–107.
    • (2003) Climate Research , vol.25 , Issue.2 , pp. 95-107
    • Crane, R.G.1    Hewitson, B.C.2
  • 31
    • 84915819235 scopus 로고    scopus 로고
    • A new iterative modularity-based method for graph clustering on scalable networks
    • 2562
    • Cui, Y., Zhang, B., & Rao, G., (2014). A new iterative modularity-based method for graph clustering on scalable networks. Applied Mechanics & Materials, 644–650, 2562.
    • (2014) Applied Mechanics & Materials , pp. 644-650
    • Cui, Y.1    Zhang, B.2    Rao, G.3
  • 34
    • 84879085176 scopus 로고    scopus 로고
    • Ant colony optimization
    • New York, NY, USA: Springer, &
    • Dorigo, M., & Birattari, M., (2010). Ant colony optimization. In Encyclopedia of machine learning (pp. 36–39). New York, NY, USA: Springer.
    • (2010) Encyclopedia of machine learning , pp. 36-39
    • Dorigo, M.1    Birattari, M.2
  • 36
    • 34347333289 scopus 로고    scopus 로고
    • A local-density based spatial clustering algorithm with noise
    • Duan, L., Xu, L., Guo, F., Lee, J., & Yan, B., (2007). A local-density based spatial clustering algorithm with noise. Information Systems, 32(7), 978–986.
    • (2007) Information Systems , vol.32 , Issue.7 , pp. 978-986
    • Duan, L.1    Xu, L.2    Guo, F.3    Lee, J.4    Yan, B.5
  • 39
    • 84879467545 scopus 로고    scopus 로고
    • Speeding up correlation search for binary data
    • Duan, L., Street, W. N., & Liu, Y., (2013). Speeding up correlation search for binary data. Pattern Recognition Letters, 34(13), 1499–1507.
    • (2013) Pattern Recognition Letters , vol.34 , Issue.13 , pp. 1499-1507
    • Duan, L.1    Street, W.N.2    Liu, Y.3
  • 41
    • 85055298348 scopus 로고
    • Accurate methods for the statistics of surprise and coincidence
    • Dunning, T., (1993). Accurate methods for the statistics of surprise and coincidence. Computational Linguistics, 19(1), 61–74.
    • (1993) Computational Linguistics , vol.19 , Issue.1 , pp. 61-74
    • Dunning, T.1
  • 44
    • 84872431330 scopus 로고    scopus 로고
    • View of MapReduce: Programming model, methods, and its applications
    • Fang, W., Pan, W., & Cui, Z., (2012). View of MapReduce: Programming model, methods, and its applications. IETE Technical Review, 29(5), 380–387.
    • (2012) IETE Technical Review , vol.29 , Issue.5 , pp. 380-387
    • Fang, W.1    Pan, W.2    Cui, Z.3
  • 46
    • 33749319347 scopus 로고    scopus 로고
    • Interestingness measures for data mining: A survey
    • Geng, L., & Hamilton, H. J., (2006). Interestingness measures for data mining: A survey. ACM Computing Surveys (CSUR), 38(3), 9.
    • (2006) ACM Computing Surveys (CSUR) , vol.38 , Issue.3 , pp. 9
    • Geng, L.1    Hamilton, H.J.2
  • 49
    • 0004215426 scopus 로고    scopus 로고
    • Boston: Kluwer Academic Publishers
    • Glover, F., & Laguna, M., (1999). Tabu search. Boston: Kluwer Academic Publishers.
    • (1999) Tabu search
    • Glover, F.1    Laguna, M.2
  • 52
    • 0034228041 scopus 로고    scopus 로고
    • ROCK: A robust clustering algorithm for categorical attributes
    • Guha, S., Rastogi, R., & Shim, K., (2000). ROCK: A robust clustering algorithm for categorical attributes. Information Systems, 25(5), 345–366.
    • (2000) Information Systems , vol.25 , Issue.5 , pp. 345-366
    • Guha, S.1    Rastogi, R.2    Shim, K.3
  • 54
  • 57
    • 38049052212 scopus 로고    scopus 로고
    • Denclue 2.0: Fast clustering based on kernel density estimation
    • Berthold M.R., Shawe-Taylor J., Lavrac N., (eds), Ljubljana, Slovenia: Springer, &
    • Hinneburg, A., & Gabriel, H.-H., (2007). Denclue 2.0: Fast clustering based on kernel density estimation. In Proceedings of the Seventh International Symposium on Intelligent Data Analysis, ed. Berthold, MR, Shawe-Taylor, J., Lavrac, N., 70–80. Ljubljana, Slovenia: Springer.
    • (2007) Proceedings of the Seventh International Symposium on Intelligent Data Analysis , pp. 70-80
    • Hinneburg, A.1    Gabriel, H.-H.2
  • 58
    • 0000835955 scopus 로고    scopus 로고
    • Proceedings of the 25th International Conference on Very Large Data Bases
    • Tkinson M.P., Orlowska M.E., Valduriez P., Zdonik S.B., Brodie M.L., (eds), Morgan Kaufmann, Edinburgh, UK:, &
    • Hinneburg, A., & Keim, D. A., (1999). Optimal grid-clustering: Towards breaking the curse of dimensionality in high-dimensional clustering. In Proceedings of the 25th International Conference on Very Large Data Bases, ed. Tkinson, MP, Orlowska, M. E., Valduriez, P., Zdonik, S. B., Brodie, M. L., 506–17. Morgan Kaufmann, Edinburgh, UK.
    • (1999) Optimal grid-clustering: Towards breaking the curse of dimensionality in high-dimensional clustering , pp. 506-517
    • Hinneburg, A.1    Keim, D.A.2
  • 60
    • 84902011113 scopus 로고    scopus 로고
    • Network-based modeling and analysis of systemic risk in banking systems
    • Hu, D., Zhao, J. L., Hua, Z., & Wong, M. C. (2012). Network-based modeling and analysis of systemic risk in banking systems. MIS Quarterly, 36(4), 1269–1291.
    • (2012) MIS Quarterly , vol.36 , Issue.4 , pp. 1269-1291
    • Hu, D.1    Zhao, J.L.2    Hua, Z.3    Wong, M.C.4
  • 61
    • 27144536001 scopus 로고    scopus 로고
    • Extensions to the k-means algorithm for clustering large data sets with categorical values
    • Huang, Z., (1998). Extensions to the k-means algorithm for clustering large data sets with categorical values. Data Mining and Knowledge Discovery, 2(3), 283–304.
    • (1998) Data Mining and Knowledge Discovery , vol.2 , Issue.3 , pp. 283-304
    • Huang, Z.1
  • 62
    • 0032595161 scopus 로고    scopus 로고
    • A fuzzy k-modes algorithm for clustering categorical data
    • Huang, Z., & Ng, M. K., (1999). A fuzzy k-modes algorithm for clustering categorical data. IEEE Transactions on Fuzzy Systems, 7(4), 446–452.
    • (1999) IEEE Transactions on Fuzzy Systems , vol.7 , Issue.4 , pp. 446-452
    • Huang, Z.1    Ng, M.K.2
  • 66
    • 71149088987 scopus 로고    scopus 로고
    • Users of the world, unite! The challenges and opportunities of social media
    • Kaplan, A. M., & Haenlein, M., (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68.
    • (2010) Business Horizons , vol.53 , Issue.1 , pp. 59-68
    • Kaplan, A.M.1    Haenlein, M.2
  • 68
    • 0032686723 scopus 로고    scopus 로고
    • Chameleon: Hierarchical clustering using dynamic modeling
    • Karypis, G., Han, E.-H., & Kumar, V., (1999). Chameleon: Hierarchical clustering using dynamic modeling. Computer, 32(8), 68–75.
    • (1999) Computer , vol.32 , Issue.8 , pp. 68-75
    • Karypis, G.1    Han, E.-H.2    Kumar, V.3
  • 69
    • 84886563124 scopus 로고    scopus 로고
    • Particle swarm optimization
    • US: Springer
    • Kennedy, J., (2010). Particle swarm optimization. In Encyclopedia of machine learning (pp. 760–766). US: Springer.
    • (2010) Encyclopedia of machine learning , pp. 760-766
    • Kennedy, J.1
  • 70
    • 0026995495 scopus 로고
    • Proceedings of the tenth national conference on artificial intelligence, San Jose, CA: AAAI Press
    • Kerber, R., (1992). Chimerge: Discretization of numeric attributes. In Proceedings of the tenth national conference on artificial intelligence, 123–28. San Jose, CA: AAAI Press.
    • (1992) Chimerge: Discretization of numeric attributes , pp. 123-128
    • Kerber, R.1
  • 71
    • 33751432287 scopus 로고    scopus 로고
    • Data mining techniques for the detection of fraudulent financial statements
    • Kirkos, E., Spathis, C., & Manolopoulos, Y., (2007). Data mining techniques for the detection of fraudulent financial statements. Expert Systems with Applications, 32(4), 995–1003.
    • (2007) Expert Systems with Applications , vol.32 , Issue.4 , pp. 995-1003
    • Kirkos, E.1    Spathis, C.2    Manolopoulos, Y.3
  • 72
    • 0001849163 scopus 로고
    • Shisha O., (ed), New York: Inequalities Ill, Academic Press
    • Klee, V., & Minty, G. J., (1970). How good is the simplex algorithm. ed. Shisha, O, 159–79. New York: Inequalities Ill, Academic Press.
    • (1970) How good is the simplex algorithm , pp. 159-179
    • Klee, V.1    Minty, G.J.2
  • 75
    • 84868021575 scopus 로고    scopus 로고
    • Web 2.0 environmental scanning and adaptive decision support for business mergers and acquisitions
    • Lau, R. Y., Liao, S. S., Wong, K.-F., & Chiu, D. K. (2012). Web 2.0 environmental scanning and adaptive decision support for business mergers and acquisitions. MIS Quarterly, 36(4), 1239–1268.
    • (2012) MIS Quarterly , vol.36 , Issue.4 , pp. 1239-1268
    • Lau, R.Y.1    Liao, S.S.2    Wong, K.-F.3    Chiu, C.4
  • 77
    • 84055180363 scopus 로고    scopus 로고
    • Next-generation smartphones technology trend analysis
    • In
    • Lee, J., Jin, A., & Park, Y., (2011). Next-generation smartphones technology trend analysis. In KIPS Conference vol. 18(1).
    • (2011) KIPS Conference , vol.18 , Issue.1
    • Lee, J.1    Jin, A.2    Park, Y.3
  • 78
    • 0001457509 scopus 로고
    • Neyman L.M.L.C.J., (ed), Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, Oakland, CA, USA: University of California Press
    • MacQueen, J., (1967). Some methods for classification and analysis of multivariate observations. In Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, ed. Neyman, LMLCJ, 281–97. Oakland, CA, USA: University of California Press.
    • (1967) Some methods for classification and analysis of multivariate observations , pp. 281-297
    • MacQueen, J.1
  • 79
    • 84860443491 scopus 로고    scopus 로고
    • From databases to big data
    • Madden, S., (2012). From databases to big data. IEEE Internet Computing, 16(3), 4–6.
    • (2012) IEEE Internet Computing , vol.16 , Issue.3 , pp. 4-6
    • Madden, S.1
  • 81
    • 84928555455 scopus 로고    scopus 로고
    • Managing, analysing, and integrating big data in medical bioinformatics: Open problems and future perspectives
    • Merelli, I., Pérez-Sánchez, H., Gesing, S., & D'agostino, D., (2014). Managing, analysing, and integrating big data in medical bioinformatics: Open problems and future perspectives. BioMed Research International 2014: 1–13.
    • (2014) BioMed Research International , pp. 1-13
    • Merelli, I.1    Pérez-Sánchez, H.2    Gesing, S.3    D'agostino, D.4
  • 82
    • 34250124910 scopus 로고
    • Massively parallel processing
    • Metropolis, N., (1986). Massively parallel processing. Journal of Scientific Computing, 1(2), 115–116.
    • (1986) Journal of Scientific Computing , vol.1 , Issue.2 , pp. 115-116
    • Metropolis, N.1
  • 83
    • 85056999934 scopus 로고    scopus 로고
    • Museth K., Möller T., Möller T., Ynnerman A., Ynnerman A., (eds), Proceedings of the 9th Joint Eurographics - IEEE VGTC Symposium on Visualization (EuroVis 2007), Norrköping, Sweden: Aire-la-Ville: Eurographics Association, &
    • Moreta, S., & Telea, A., (2007). Multiscale visualization of dynamic software logs. In Proceedings of the 9th Joint Eurographics - IEEE VGTC Symposium on Visualization (EuroVis 2007). ed. K., Museth, KM, T., Möller, T., Möller, A., Ynnerman & A., Ynnerman, 11–18. Norrköping, Sweden: Aire-la-Ville: Eurographics Association.
    • (2007) Multiscale visualization of dynamic software logs , pp. 11-18
    • Moreta, S.1    Telea, A.2
  • 84
    • 33845532853 scopus 로고    scopus 로고
    • Memetic algorithms
    • Onwubolu G.C., Babu B.V., (eds), Springer-Verlag, Berlin Heidelberg:, &
    • Moscato, P., Cotta, C., & Mendes, A., (2004). Memetic algorithms. In New optimization techniques in engineering, ed. Onwubolu, G. C., Babu, B. V., 53–85: Springer-Verlag, Berlin Heidelberg.
    • (2004) New optimization techniques in engineering , pp. 53-85
    • Moscato, P.1    Cotta, C.2    Mendes, A.3
  • 87
    • 0036709106 scopus 로고    scopus 로고
    • Clarans: A method for clustering objects for spatial data mining
    • Ng, R. T., & Han, J., (2002). Clarans: A method for clustering objects for spatial data mining. IEEE Transactions on Knowledge and Data Engineering, 14(5), 1003–1016.
    • (2002) IEEE Transactions on Knowledge and Data Engineering , vol.14 , Issue.5 , pp. 1003-1016
    • Ng, R.T.1    Han, J.2
  • 88
    • 78651084785 scopus 로고    scopus 로고
    • The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature
    • Ngai, E. W. T., Hu, Y., Wong, Y. H., Chen, Y., & Sun, X., (2011). The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature. Decision Support Systems, 50(3), 559–569.
    • (2011) Decision Support Systems , vol.50 , Issue.3 , pp. 559-569
    • Ngai, E.W.T.1    Hu, Y.2    Wong, Y.H.3    Chen, Y.4    Sun, X.5
  • 89
    • 84868007552 scopus 로고    scopus 로고
    • A social network-based inference model for validating customer profile data
    • Park, S.-H., Huh, S.-Y., Oh, W., & Han, S. P., (2012). A social network-based inference model for validating customer profile data. MIS Quarterly, 36(4), 1217–1237.
    • (2012) MIS Quarterly , vol.36 , Issue.4 , pp. 1217-1237
    • Park, S.-H.1    Huh, S.-Y.2    Oh, W.3    Han, S.P.4
  • 92
    • 33744584654 scopus 로고
    • Induction of decision trees
    • Quinlan, J. R., (1986). Induction of decision trees. Machine Learning, 1(1), 81–106.
    • (1986) Machine Learning , vol.1 , Issue.1 , pp. 81-106
    • Quinlan, J.R.1
  • 93
    • 0001495905 scopus 로고
    • 5th Australian joint conference on artificial intelligence (AI 1992), Singapore
    • Quinlan, J. R., (1992). Learning with continuous classes. In 5th Australian joint conference on artificial intelligence (AI 1992), 343–348: Singapore.
    • (1992) Learning with continuous classes , pp. 343-348
    • Quinlan, J.R.1
  • 96
    • 0024610919 scopus 로고
    • A tutorial on hidden Markov models and selected applications in speech recognition
    • Rabiner, L., (1989). A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE, 77(2), 257–286.
    • (1989) Proceedings of the IEEE , vol.77 , Issue.2 , pp. 257-286
    • Rabiner, L.1
  • 98
    • 78650176118 scopus 로고    scopus 로고
    • Detection of financial statement fraud and feature selection using data mining techniques
    • Ravisankar, P., Ravi, V., Raghava Rao, G., & Bose, I. (2011). Detection of financial statement fraud and feature selection using data mining techniques. Decision Support Systems, 50(2), 491–500.
    • (2011) Decision Support Systems , vol.50 , Issue.2 , pp. 491-500
    • Ravisankar, P.1    Ravi, R.2    Raghava Rao, G.3    Bose, I.4
  • 99
    • 32444435813 scopus 로고    scopus 로고
    • Radio frequency identification (RFID)
    • Roberts, C. M., (2006). Radio frequency identification (RFID). Computers & Security, 25(1), 18–26.
    • (2006) Computers & Security , vol.25 , Issue.1 , pp. 18-26
    • Roberts, C.M.1
  • 100
    • 0001319911 scopus 로고
    • Proceedings of the Third Text REtrieval Conference(TREC-3), NIST Special Publication 500-225, Washington D.C:, &
    • Robertson, S. E., Walker, S., Jones, S., Hancock-Beaulieu, M. M., & Gatford, M. (1995). Okapi at TREC-3. In Proceedings of the Third Text REtrieval Conference(TREC-3), NIST Special Publication 500-225, 109–26. Washington D.C.
    • (1995) Okapi at TREC-3 , pp. 109-126
    • Robertson, S.E.1    Walker, W.2    Jones, J.3    Hancock-Beaulieu, H.-B.4    Gatford, G.5
  • 103
    • 84863610828 scopus 로고    scopus 로고
    • Renton, WA: The Data Warehousing Institute (TDWI) Best Practices Report
    • Russom, P., (2011). Big data analytics. Renton, WA: The Data Warehousing Institute (TDWI) Best Practices Report.
    • (2011) Big data analytics
    • Russom, P.1
  • 104
    • 84937439575 scopus 로고    scopus 로고
    • Renton, WA: The Data Warehousing Institute (TDWI) Best Practices Report
    • Russom, P., (2013). Managing big data. Renton, WA: The Data Warehousing Institute (TDWI) Best Practices Report.
    • (2013) Managing big data
    • Russom, P.1
  • 105
    • 19044371729 scopus 로고
    • Testing for unit roots in autoregressive-moving average models of unknown order
    • Said, S. E., & Dickey, D. A., (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599–607.
    • (1984) Biometrika , vol.71 , Issue.3 , pp. 599-607
    • Said, S.E.1    Dickey, D.A.2
  • 108
    • 85056990470 scopus 로고
    • Korte B., (ed), North-Holland, Amsterdam: Modern Applied Mathematics - Optimization and Operations Research
    • Schrader, R., (1981). Ellipsoid methods, ed. Korte, B, 265–311. North-Holland, Amsterdam: Modern Applied Mathematics - Optimization and Operations Research.
    • (1981) Ellipsoid methods , pp. 265-311
    • Schrader, R.1
  • 109
    • 77957825754 scopus 로고    scopus 로고
    • An analytic approach to select data mining for business decision
    • Seng, J.-L., & Chen, T. C., (2010). An analytic approach to select data mining for business decision. Expert Systems with Applications, 37(12), 8042–8057.
    • (2010) Expert Systems with Applications , vol.37 , Issue.12 , pp. 8042-8057
    • Seng, J.-L.1    Chen, T.C.2
  • 110
    • 84968497764 scopus 로고
    • Conditioning of quasi-Newton methods for function minimization
    • Shanno, D. F., (1970). Conditioning of quasi-Newton methods for function minimization. Mathematics of Computation, 24(111), 647–656.
    • (1970) Mathematics of Computation , vol.24 , Issue.111 , pp. 647-656
    • Shanno, D.F.1
  • 111
    • 0003052357 scopus 로고    scopus 로고
    • Wavecluster: A multi-resolution clustering approach for very large spatial databases
    • New York City, New York: Morgan Kaufmann Publishers Inc, &
    • Sheikholeslami, G., Chatterjee, S., & Zhang, A., (1998). Wavecluster: A multi-resolution clustering approach for very large spatial databases. In Proceedings of the 24th International Conference on Very Large Data Bases, 428–39. New York City, New York: Morgan Kaufmann Publishers Inc.
    • (1998) Proceedings of the 24th International Conference on Very Large Data Bases , pp. 428-439
    • Sheikholeslami, G.1    Chatterjee, S.2    Zhang, A.3
  • 114
    • 0013126801 scopus 로고
    • fourth edition ed, Redwood City, CA: Benjamin/Cummings Publishing Co
    • Stamper, D. A., & Case, T., (1994). Business data communications. fourth edition ed. Redwood City, CA: Benjamin/Cummings Publishing Co.
    • (1994) Business data communications
    • Stamper, D.A.1    Case, T.2
  • 116
    • 0032638628 scopus 로고    scopus 로고
    • Least squares support vector machine classifiers
    • Suykens, J. A., & Vandewalle, J., (1999). Least squares support vector machine classifiers. Neural Processing Letters, 9(3), 293–300.
    • (1999) Neural Processing Letters , vol.9 , Issue.3 , pp. 293-300
    • Suykens, J.A.1    Vandewalle, J.2
  • 117
    • 1242308945 scopus 로고    scopus 로고
    • Selecting the right objective measure for association analysis
    • Tan, P.-N., Kumar, V., & Srivastava, J., (2004). Selecting the right objective measure for association analysis. Information Systems, 29(4), 293–313.
    • (2004) Information Systems , vol.29 , Issue.4 , pp. 293-313
    • Tan, P.-N.1    Kumar, V.2    Srivastava, J.3
  • 118
    • 84896488377 scopus 로고    scopus 로고
    • Behavior-based clustering and analysis of interestingness measures for association rule mining
    • Tew, C., Giraud-Carrier, C., Tanner, K., & Burton, S., (2014). Behavior-based clustering and analysis of interestingness measures for association rule mining. Data Mining and Knowledge Discovery, 28(4), 1004–1045.
    • (2014) Data Mining and Knowledge Discovery , vol.28 , Issue.4 , pp. 1004-1045
    • Tew, C.1    Giraud-Carrier, C.2    Tanner, K.3    Burton, S.4
  • 120
    • 33746035971 scopus 로고    scopus 로고
    • The max–min hill-climbing Bayesian network structure learning algorithm
    • Tsamardinos, I., Brown, L. E., & Aliferis, C. F., (2006). The max–min hill-climbing Bayesian network structure learning algorithm. Machine Learning, 65(1), 31–78.
    • (2006) Machine Learning , vol.65 , Issue.1 , pp. 31-78
    • Tsamardinos, I.1    Brown, L.E.2    Aliferis, C.F.3
  • 121
    • 84922674749 scopus 로고    scopus 로고
    • From insight to action
    • Udell, M., (2014). From insight to action. Marketing Insights, 26(6), 38–43.
    • (2014) Marketing Insights , vol.26 , Issue.6 , pp. 38-43
    • Udell, M.1
  • 123
    • 0010864753 scopus 로고
    • Pattern recognition using generalized portrait method
    • Vapnik, V., (1963). Pattern recognition using generalized portrait method. Automation and Remote Control, 24, 774–780.
    • (1963) Automation and Remote Control , vol.24 , pp. 774-780
    • Vapnik, V.1
  • 127
    • 84900822860 scopus 로고    scopus 로고
    • Click here for a data scientist: Big data, predictive analytics, and theory development in the era of a maker movement supply chain
    • Waller, M. A., & Fawcett, S. E., (2013a). Click here for a data scientist: Big data, predictive analytics, and theory development in the era of a maker movement supply chain. Journal of Business Logistics, 34(4), 249–252.
    • (2013) Journal of Business Logistics , vol.34 , Issue.4 , pp. 249-252
    • Waller, M.A.1    Fawcett, S.E.2
  • 128
    • 84900796645 scopus 로고    scopus 로고
    • Data science, predictive analytics, and big data: A revolution that will transform supply chain design and management
    • Waller, M. A., & Fawcett, S. E., (2013b). Data science, predictive analytics, and big data: A revolution that will transform supply chain design and management. Journal of Business Logistics, 34(2), 77–84.
    • (2013) Journal of Business Logistics , vol.34 , Issue.2 , pp. 77-84
    • Waller, M.A.1    Fawcett, S.E.2
  • 129
    • 34548293679 scopus 로고    scopus 로고
    • Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy
    • Wang, Q., Garrity, G. M., Tiedje, J. M., & Cole, J. R. (2007). Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and Environmental Microbiology, 73(16), 5261–5267.
    • (2007) Applied and Environmental Microbiology , vol.73 , Issue.16 , pp. 5261-5267
    • Wang, Q.1    G. M, G.2    J. M, T.3    J. R, C.4
  • 131
    • 50849123367 scopus 로고
    • What is the Laplace transform?
    • 52, no 8
    • Widder, D. V., (1945). What is the Laplace transform? American Mathematical Monthly, 52, no 8: 419–425.
    • (1945) American Mathematical Monthly , pp. 419-425
    • Widder, D.V.1
  • 135
    • 0036487285 scopus 로고    scopus 로고
    • Why can LDA be performed in PCA transformed space?
    • Yang, J., & Yang, J.-Y., (2003). Why can LDA be performed in PCA transformed space? Pattern Recognition, 36(2), 563–566.
    • (2003) Pattern Recognition , vol.36 , Issue.2 , pp. 563-566
    • Yang, J.1    Yang, J.-Y.2
  • 138
    • 0033221733 scopus 로고    scopus 로고
    • Evolutionary programming based optimal power flow algorithm
    • Yuryevich, J., & Wong, K. P., (1999). Evolutionary programming based optimal power flow algorithm. IEEE Transactions on Power Systems, 14(4), 1245–1250.
    • (1999) IEEE Transactions on Power Systems , vol.14 , Issue.4 , pp. 1245-1250
    • Yuryevich, J.1    Wong, K.P.2
  • 141
    • 0030157145 scopus 로고    scopus 로고
    • BIRCH: An efficient data clustering method for very large databases
    • Montreal, Canada: Association for Computing Machinery (ACM), &
    • Zhang, T., Ramakrishnan, R., & Livny, M., (1996). BIRCH: An efficient data clustering method for very large databases. In ACM Sigmod Record (Special Interest Group on Management of Data), 103–14. Montreal, Canada: Association for Computing Machinery (ACM).
    • (1996) ACM Sigmod Record (Special Interest Group on Management of Data) , pp. 103-114
    • Zhang, T.1    Ramakrishnan, R.2    Livny, M.3
  • 142


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