- Acito, F.; Khatri, V. Business Analytics: Why Now and What Next? Bus. Horiz. 2014, 57, 565–570. [CrossRef]
Paper not yet in RePEc: Add citation now
- Ackley, D.H.; Hinton, G.E.; Sejnowski, T.J. A Learning Algorithm for Boltzmann Machines. Cogn. Sci. 1985, 9, 147–169. [CrossRef]
Paper not yet in RePEc: Add citation now
- Agrawal, R.; Gehrke, J.; Gunopulos, D.; Raghavan, P. Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications. In SIGMOD 098 Proceedings of the 1998 ACM SIGMOD international conference on Management of data, Seattle, WA, USA, 1-4 June 1998; ACM: New York, NY, USA, 1998; pp. 94–105.
Paper not yet in RePEc: Add citation now
- Akil, B.; Zhou, Y.; Röhm, U. On the Usability of Hadoop MapReduce, Apache Spark & Apache Flink for Data Science. In Proceedings of the 2017 IEEE International Conference on Big Data (Big Data), Boston, MA, USA, 11–14 December 2017; pp. 303–310.
Paper not yet in RePEc: Add citation now
- Ankerst, M.; Breunig, M.M.; Kriegel, H.-P.; Sander, J. OPTICS: Ordering Points to Identify the Clustering Structure. ACM Sigmod Rec. 1999, 28, 49–60. [CrossRef]
Paper not yet in RePEc: Add citation now
Appelbaum, D.; Kogan, A.; Vasarhelyi, M.; Yan, Z. Impact of Business Analytics and Enterprise Systems on Managerial Accounting. Int. J. Account. Inf. Syst. 2017, 25, 29–44. [CrossRef]
Arifovic, J. Genetic Algorithm Learning and the Cobweb Model. J. Econ. Dyn. Control. 1994, 18, 3–28. [CrossRef]
Batt, S.; Grealis, T.; Harmon, O.; Tomolonis, P. Learning Tableau: A Data Visualization Tool. J. Econ. Educ. 2020, 51, 317–328. [CrossRef]
- Bayrak, T. A Review of Business Analytics: A Business Enabler or Another Passing Fad. Procedia-Soc. Behav. Sci. 2015, 195, 230–239. [CrossRef]
Paper not yet in RePEc: Add citation now
- Bezdek, J.C.; Ehrlich, R.; Full, W. FCM: The Fuzzy c-Means Clustering Algorithm. Comput. Geosci. 1984, 10, 191–203. [CrossRef]
Paper not yet in RePEc: Add citation now
- Boute, R.N.; Gijsbrechts, J.; van Jaarsveld, W.; Vanvuchelen, N. Deep Reinforcement Learning for Inventory Control: A Roadmap. Eur. J. Oper. Res. 2021, 298, 401–412. [CrossRef]
Paper not yet in RePEc: Add citation now
- Box, G.E.P.; Jenkins, G.M.; Reinsel, G.C. Time Series Analysis: Forecasting and Control, 3rd ed.; Prentice Hall: Englewood Cliffs, NJ, USA, 1994; ISBN 978-0-13-060774-4.
Paper not yet in RePEc: Add citation now
- Breiman, L. Random Forests. Mach. Learn. 2001, 45, 5–32. [CrossRef]
Paper not yet in RePEc: Add citation now
- Brin, S.; Motwani, R.; Ullman, J.D.; Tsur, S. Dynamic Itemset Counting and Implication Rules for Market Basket Data. In Proceedings of the 1997 ACM SIGMOD International Conference on Management of Data, Tucson, AZ, USA, 13–15 May 1997; pp. 255–264.
Paper not yet in RePEc: Add citation now
- Chen, D.; Lai, C.; Hu, W.; Chen, W.; Zhang, Y.; Zheng, W. Tree Partition Based Parallel Frequent Pattern Mining on Shared Memory Systems. In Proceedings of the 20th IEEE International Parallel & Distributed Processing Symposium, Rhodes Island, Greece, 25–29 April 2006; p. 8.
Paper not yet in RePEc: Add citation now
- Chen, H.; Chiang, R.H.; Storey, V.C. Business Intelligence and Analytics: From Big Data to Big Impact. MIS Q. 2012, 36, 1165–1188. [CrossRef]
Paper not yet in RePEc: Add citation now
- Chen, T.; Guestrin, C. Xgboost: A Scalable Tree Boosting System. In KDD 016 Proceedings of the 22nd acm sigkdd international conference on knowledge discovery and data mining, San Francisco, CA, USA, 13–17 August 2016; ACM: New York, NY, USA, 2016; pp. 785–794.
Paper not yet in RePEc: Add citation now
- Commission, E. A New Circular Economy Action Plan; Office of the European Union Brussels: Brussels, Belgium, 2020; pp. 1–19.
Paper not yet in RePEc: Add citation now
- Cover, T.; Hart, P. Nearest Neighbor Pattern Classification. IEEE Trans. Inf. Theory 1967, 13, 21–27. [CrossRef]
Paper not yet in RePEc: Add citation now
- Davenport, T.H.; Harris, J.G. Competing on Analytics: The New Science of Winning. Language 2007, 15, 24.
Paper not yet in RePEc: Add citation now
- de Oliveira, M.P.V.; McCormack, K.; Trkman, P. Business Analytics in Supply Chains—The Contingent Effect of Business Process Maturity. Expert Syst. Appl. 2012, 39, 5488–5498. [CrossRef]
Paper not yet in RePEc: Add citation now
- Delen, D.; Ram, S. Research Challenges and Opportunities in Business Analytics. J. Bus. Anal. 2018, 1, 2–12. [CrossRef]
Paper not yet in RePEc: Add citation now
Delen, D.; Zolbanin, H.M. The Analytics Paradigm in Business Research. J. Bus. Res. 2018, 90, 186–195. [CrossRef]
- Dennis, J.; Moré, J.J. Quasi-Newton Methods, Motivation and Theory. SIAM Rev. 1977, 19, 46–89. [CrossRef]
Paper not yet in RePEc: Add citation now
- DeVore, R.A.; Temlyakov, V.N. Some Remarks on Greedy Algorithms. Adv. Comput. Math. 1996, 5, 173–187. [CrossRef]
Paper not yet in RePEc: Add citation now
- Dorigo, M.; Birattari, M.; Stutzle, T. Ant Colony Optimization. IEEE Comput. Intell. Mag. 2006, 1, 28–39. [CrossRef]
Paper not yet in RePEc: Add citation now
- Dorogush, A.V.; Ershov, V.; Gulin, A. CatBoost: Gradient Boosting with Categorical Features Support. arXiv 2018, arXiv:1810.11363.
Paper not yet in RePEc: Add citation now
- Duan, L.; Xiong, Y. Big Data Analytics and Business Analytics. J. Manag. Anal. 2015, 2, 1–21. [CrossRef]
Paper not yet in RePEc: Add citation now
- Ester, M.; Kriegel, H.-P.; Sander, J.; Xu, X. Density-Based Spatial Clustering of Applications with Noise. In Proceedings of the Second International Conference Knowledge Discovery and Data Mining, Portland, OR, USA, 2–4 August 1996; Volume 240.
Paper not yet in RePEc: Add citation now
Fanelli, D.; Piazza, F. Analysis and Forecast of COVID-19 Spreading in China, Italy and France. Chaos Solitons Fractals 2020, 134, 109761. [CrossRef] [PubMed]
- Freund, Y.; Schapire, R.; Abe, N. A Short Introduction to Boosting. J.-Jpn. Soc. Artif. Intell. 1999, 14, 1612.
Paper not yet in RePEc: Add citation now
- Freund, Y.; Schapire, R.E. A Decision-Theoretic Generalization of on-Line Learning and an Application to Boosting. J. Comput. Syst. Sci. 1997, 55, 119–139. [CrossRef]
Paper not yet in RePEc: Add citation now
- Friedman, J.H. Greedy Function Approximation: A Gradient Boosting Machine. Ann. Stat. 2001, 29, 1189–1232. [CrossRef]
Paper not yet in RePEc: Add citation now
- Gardner, E.S. Exponential Smoothing: The State of the Art. J. Forecast. 1985, 4, 1–28. [CrossRef]
Paper not yet in RePEc: Add citation now
- Gerrard, M.; Gibbons, F.X.; Houlihan, A.E.; Stock, M.L.; Pomery, E.A. A Dual-Process Approach to Health Risk Decision Making: The Prototype Willingness Model. Dev. Rev. 2008, 28, 29–61. [CrossRef]
Paper not yet in RePEc: Add citation now
- Gers, F.A.; Schmidhuber, J.; Cummins, F. Learning to Forget: Continual Prediction with LSTM. Neural Comput. 2000, 12, 2451–2471. [CrossRef] [PubMed]
Paper not yet in RePEc: Add citation now
- Glover, F.; Laguna, M. Tabu Search. In Handbook of Combinatorial Optimization; Springer: Berlin/Heidelberg, Germany, 1998; pp. 2093–2229.
Paper not yet in RePEc: Add citation now
- Gopalsamy, K.; He, X. Stability in Asymmetric Hopfield Nets with Transmission Delays. Phys. D Nonlinear Phenom. 1994, 76, 344–358. [CrossRef]
Paper not yet in RePEc: Add citation now
- Griva, A.; Bardaki, C.; Pramatari, K.; Papakiriakopoulos, D. Retail Business Analytics: Customer Visit Segmentation Using Market Basket Data. Expert Syst. Appl. 2018, 100, 1–16. [CrossRef]
Paper not yet in RePEc: Add citation now
- Guha, S.; Rastogi, R.; Shim, K. CURE: An Efficient Clustering Algorithm for Large Databases. ACM Sigmod Rec. 1998, 27, 73–84. [CrossRef]
Paper not yet in RePEc: Add citation now
- Guha, S.; Rastogi, R.; Shim, K. ROCK: A Robust Clustering Algorithm for Categorical Attributes. Inf. Syst. 2000, 25, 345–366. [CrossRef]
Paper not yet in RePEc: Add citation now
Harzing, A.-W.; Alakangas, S. Google Scholar, Scopus and the Web of Science: A Longitudinal and Cross-Disciplinary Comparison. Scientometrics 2016, 106, 787–804. [CrossRef]
- Hinneburg, A.; Keim, D.A. An Efficient Approach to Clustering in Large Multimedia Databases with Noise; Bibliothek der Universität Konstanz: Konstanz, Germany, 1998; Volume 98.
Paper not yet in RePEc: Add citation now
- Holsapple, C.; Lee-Post, A.; Pakath, R. A Unified Foundation for Business Analytics. Decis. Support Syst. 2014, 64, 130–141. [CrossRef]
Paper not yet in RePEc: Add citation now
- Hosmer, D.W., Jr.; Lemeshow, S.; Sturdivant, R.X. Applied Logistic Regression; John Wiley & Sons: Hoboken, NJ, USA, 2013; Volume 398, ISBN 0-470-58247-2.
Paper not yet in RePEc: Add citation now
- Huang, C.-J.; Kuo, P.-H. A Deep CNN-LSTM Model for Particulate Matter (PM2. 5) Forecasting in Smart Cities. Sensors 2018, 18, 2220. [CrossRef] [PubMed]
Paper not yet in RePEc: Add citation now
- Huang, Z.; Ng, M.K. A Fuzzy K-Modes Algorithm for Clustering Categorical Data. IEEE Trans. Fuzzy Syst. 1999, 7, 446–452. [CrossRef]
Paper not yet in RePEc: Add citation now
- Hwangbo, H.; Kim, Y.S.; Cha, K.J. Recommendation System Development for Fashion Retail E-Commerce. Electron. Commer. Res. Appl. 2018, 28, 94–101. [CrossRef]
Paper not yet in RePEc: Add citation now
Hyndman, R.J.; Koehler, A.B.; Snyder, R.D.; Grose, S. A State Space Framework for Automatic Forecasting Using Exponential Smoothing Methods. Int. J. Forecast. 2002, 18, 439–454. [CrossRef]
- INFORMS. Certified Analytics Professional Handbook; INFORMS: Catonsville, MD, USA, 2016.
Paper not yet in RePEc: Add citation now
- Isinkaye, F.O.; Folajimi, Y.O.; Ojokoh, B.A. Recommendation Systems: Principles, Methods and Evaluation. Egypt. Inform. J. 2015, 16, 261–273. [CrossRef]
Paper not yet in RePEc: Add citation now
- Jain, G.; Mallick, B. A Study of Time Series Models ARIMA and ETS. SSRN J. 2017. [CrossRef]
Paper not yet in RePEc: Add citation now
- Jiang, H.; Ching, W.-K.; Yiu, K.F.C.; Qiu, Y. Stationary Mahalanobis Kernel SVM for Credit Risk Evaluation. Appl. Soft Comput. 2018, 71, 407–417. [CrossRef]
Paper not yet in RePEc: Add citation now
- Jianying, F.; Bianyu, Y.; Xin, L.; Dong, T.; Weisong, M. Evaluation on Risks of Sustainable Supply Chain Based on Optimized BP Neural Networks in Fresh Grape Industry. Comput. Electron. Agric. 2021, 183, 105988. [CrossRef]
Paper not yet in RePEc: Add citation now
- Johnson, D.S.; Papadimitriou, C.H.; Yannakakis, M. How Easy Is Local Search? J. Comput. Syst. Sci. 1988, 37, 79–100. [CrossRef]
Paper not yet in RePEc: Add citation now
- Karypis, G.; Han, E.-H.; Kumar, V. Chameleon: Hierarchical Clustering Using Dynamic Modeling. Computer 1999, 32, 68–75. [CrossRef]
Paper not yet in RePEc: Add citation now
- Kaufman, L.; Rousseeuw, P.J. (Eds.) Finding Groups in Data; Wiley Series in Probability and Statistics; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 1990; ISBN 978-0-470-31680-1.
Paper not yet in RePEc: Add citation now
- Kaur, M.; Kang, S. Market Basket Analysis: Identify the Changing Trends of Market Data Using Association Rule Mining. Procedia Comput. Sci. 2016, 85, 78–85. [CrossRef]
Paper not yet in RePEc: Add citation now
- Ke, G.; Meng, Q.; Finley, T.; Wang, T.; Chen, W.; Ma, W.; Ye, Q.; Liu, T.-Y. LightGBM: A Highly Efficient Gradient Boosting Decision Tree. In Proceedings of the Advances in Neural Information Processing Systems, Long Beach, CA, USA, 4 December 2017; Volume 30, pp. 3149–3157.
Paper not yet in RePEc: Add citation now
- Kennedy, J.; Eberhart, R. Particle Swarm Optimization. In Proceedings of the ICNN’95-International Conference on Neural Networks, Perth, Australia, 27 November–1 December 1995; Volume 4, pp. 1942–1948.
Paper not yet in RePEc: Add citation now
Kim, K.; Lee, K.; Ahn, H. Predicting Corporate Financial Sustainability Using Novel Business Analytics. Sustainability 2018, 11, 64. [CrossRef]
Kim, T.-Y.; Cho, S.-B. Predicting Residential Energy Consumption Using CNN-LSTM Neural Networks. Energy 2019, 182, 72–81. [CrossRef]
- Kirkpatrick, S.; Gelatt, C.D., Jr.; Vecchi, M.P. Optimization by Simulated Annealing. Science 1983, 220, 671–680. [CrossRef] [PubMed]
Paper not yet in RePEc: Add citation now
- Klee, V.; Minty, G.J. How Good Is the Simplex Algorithm. Inequalities 1972, 3, 159–175.
Paper not yet in RePEc: Add citation now
- Kohonen, T. Self-Organizing Maps; Springer Science & Business Media: Berlin, Germany, 2012; Volume 30, ISBN 3-642-56927-7.
Paper not yet in RePEc: Add citation now
Kraus, M.; Feuerriegel, S.; Oztekin, A. Deep Learning in Business Analytics and Operations Research: Models, Applications and Managerial Implications. Eur. J. Oper. Res. 2020, 281, 628–641. [CrossRef]
- Kristoffersen, E.; Mikalef, P.; Blomsma, F.; Li, J. The Effects of Business Analytics Capability on Circular Economy Implementation, Resource Orchestration Capability, and Firm Performance. Int. J. Prod. Econ. 2021, 239, 108205. [CrossRef]
Paper not yet in RePEc: Add citation now
- Kutner, M.H.; Nachtsheim, C.J.; Neter, J.; Wasserman, W. Applied Linear Regression Models; McGraw-Hill/Irwin: New York, NY, USA, 2004; Volume 4. Mathematics 2023, 11, 899 18 of 20
Paper not yet in RePEc: Add citation now
Lee, C.S.; Cheang, P.Y.S.; Moslehpour, M. Predictive Analytics in Business Analytics: Decision Tree. Adv. Decis. Sci. 2022, 26, 1–29.
- Lewis, R.J. An Introduction to Classification and Regression Tree (CART) Analysis. In Proceedings of the Annual meeting of the society for academic emergency medicine, San Francisco, CA, USA, 22–25 May 2000; Volume 14.
Paper not yet in RePEc: Add citation now
- Li, H.; Wang, Y.; Zhang, D.; Zhang, M.; Chang, E.Y. Pfp: Parallel Fp-Growth for Query Recommendation. In RecSys 008 Proceedings of the 2008 ACM conference on Recommender systems, Lausanne, Switzerland, 23–25 October 2008; ACM Press: Lausanne, Switzerland, 2008; p. 107.
Paper not yet in RePEc: Add citation now
- Li, N.; Zeng, L.; He, Q.; Shi, Z. Parallel Implementation of Apriori Algorithm Based on Mapreduce. In Proceedings of the 2012 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, Kyoto, Japan, 8–10 August 2012; pp. 236–241.
Paper not yet in RePEc: Add citation now
- Li, S.; Jin, X.; Xuan, Y.; Zhou, X.; Chen, W.; Wang, Y.-X.; Yan, X. Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting. Adv. Neural Inf. Process. Syst. 2019, 32. [CrossRef]
Paper not yet in RePEc: Add citation now
- Lillicrap, T.P.; Hunt, J.J.; Pritzel, A.; Heess, N.; Erez, T.; Tassa, Y.; Silver, D.; Wierstra, D. Continuous Control with Deep Reinforcement Learning. arXiv 2015, arXiv:1509.02971.
Paper not yet in RePEc: Add citation now
Lim, B.; Arık, S.Ö.; Loeff, N.; Pfister, T. Temporal Fusion Transformers for Interpretable Multi-Horizon Time Series Forecasting. Int. J. Forecast. 2021, 37, 1748–1764. [CrossRef]
- Lin, C.-W.; Hong, T.-P.; Lu, W.-H. Linguistic Data Mining with Fuzzy FP-Trees. Expert Syst. Appl. 2010, 37, 4560–4567. [CrossRef]
Paper not yet in RePEc: Add citation now
- Lu, W.; Li, J.; Li, Y.; Sun, A.; Wang, J. A CNN-LSTM-Based Model to Forecast Stock Prices. Complexity 2020, 2020, 1–10. [CrossRef]
Paper not yet in RePEc: Add citation now
- MacQueen, J. Classification and Analysis of Multivariate Observations. In Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability, Berkeley, CA, USA, 21 June–18 July 1967; pp. 281–297.
Paper not yet in RePEc: Add citation now
- Margherita, A. Human Resources Analytics: A Systematization of Research Topics and Directions for Future Research. Hum. Resour. Manag. Rev. 2022, 32, 100795. [CrossRef]
Paper not yet in RePEc: Add citation now
Mortenson, M.J.; Doherty, N.F.; Robinson, S. Operational Research from Taylorism to Terabytes: A Research Agenda for the Analytics Age. Eur. J. Oper. Res. 2015, 241, 583–595. [CrossRef]
- Murat, H.S. A brief review of feed-forward neural networks. Commun. Fac. Sci. Univ. Ank. 2006, 50, 11–17. [CrossRef]
Paper not yet in RePEc: Add citation now
- Nair, V.; Bartunov, S.; Gimeno, F.; von Glehn, I.; Lichocki, P.; Lobov, I.; O’Donoghue, B.; Sonnerat, N.; Tjandraatmadja, C.; Wang, P.; et al. Solving Mixed Integer Programs Using Neural Networks. arXiv 2021, arXiv:2012.13349.
Paper not yet in RePEc: Add citation now
- Nam, D.; Lee, J.; Lee, H. Business Analytics Use in CRM: A Nomological Net from IT Competence to CRM Performance. Int. J. Inf. Manag. 2019, 45, 233–245. [CrossRef]
Paper not yet in RePEc: Add citation now
- Ng, R.T.; Han, J. Efficient and Effective Clustering Methods for Spatial Data Mining. In VLDB094 Proceedings of the 20th International Conference on Very Large Data Bases, Santiago de Chile, Chile, 12–15 September 1994; Morgan Kaufmann Publishers Inc.: San Francisco, CA, USA, 1994; pp. 144–155.
Paper not yet in RePEc: Add citation now
- Nielsen, S. The Impact of Business Analytics on Management Accounting. SSRN J. 2015. [CrossRef]
Paper not yet in RePEc: Add citation now
- Oreshkin, B.N.; Carpov, D.; Chapados, N.; Bengio, Y. N-BEATS: Neural Basis Expansion Analysis for Interpretable Time Series Forecasting. arXiv 2020, arXiv:1905.10437.
Paper not yet in RePEc: Add citation now
Pape, T. Prioritising Data Items for Business Analytics: Framework and Application to Human Resources. Eur. J. Oper. Res. 2016, 252, 687–698. [CrossRef]
- Park, J.S.; Chen, M.-S.; Yu, P.S. An Effective Hash-Based Algorithm for Mining Association Rules. ACM Sigmod Rec. 1995, 24, 175–186. [CrossRef]
Paper not yet in RePEc: Add citation now
- Patil, S.D.; Deshmukh, R.R.; Kirange, D.K. Adaptive Apriori Algorithm for Frequent Itemset Mining. In Proceedings of the 2016 International Conference System Modeling & Advancement in Research Trends (SMART), Moradabad, India, 25–27 November 2016; pp. 7–13.
Paper not yet in RePEc: Add citation now
- Pröllochs, N.; Feuerriegel, S. Business Analytics for Strategic Management: Identifying and Assessing Corporate Challenges via Topic Modeling. Inf. Manag. 2020, 57, 103070. [CrossRef]
Paper not yet in RePEc: Add citation now
- Qiu, H.; Gu, R.; Yuan, C.; Huang, Y. Yafim: A Parallel Frequent Itemset Mining Algorithm with Spark. In Proceedings of the 2014 IEEE International Parallel & Distributed Processing Symposium Workshops, Phoenix, AZ, USA, 19–23 May 2014; pp. 1664–1671.
Paper not yet in RePEc: Add citation now
- Qiu, Y.; Lan, Y.-J.; Xie, Q.-S. An Improved Algorithm of Mining from FP-Tree. In Proceedings of the 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826), Shanghai, China, 26–29 August 2004; Volume 4, pp. 1665–1670.
Paper not yet in RePEc: Add citation now
- Quinlan, J.R. C4. 5: Programs for Machine Learning; Elsevier: Amsterdam, The Netherlands, 2014; ISBN 0-08-050058-7.
Paper not yet in RePEc: Add citation now
- Quinlan, J.R. Discovering Rules by Induction from Large Collections of Examples. Expert Syst. Micro Electron. Age 1979.
Paper not yet in RePEc: Add citation now
- Rangapuram, S.S.; Seeger, M.W.; Gasthaus, J.; Stella, L.; Wang, Y.; Januschowski, T. Deep State Space Models for Time Series Forecasting. Adv. Neural Inf. Process. Syst. 2018, 31, 7796–7805.
Paper not yet in RePEc: Add citation now
- Rathee, S.; Kaul, M.; Kashyap, A. R-Apriori: An Efficient Apriori Based Algorithm on Spark. In PIKM 015 Proceedings of the 8th Workshop on Ph.D. Workshop in Information and Knowledge Management, Melbourne, Australia, 19 October 2015; ACM: New York, NY, USA, 2015; pp. 27–34.
Paper not yet in RePEc: Add citation now
- Reynolds, D.A. Gaussian Mixture Models. Encycl. Biom. 2009, 741, 659–663.
Paper not yet in RePEc: Add citation now
Rikhardsson, P.; Yigitbasioglu, O. Business Intelligence & Analytics in Management Accounting Research: Status and Future Focus. Int. J. Account. Inf. Syst. 2018, 29, 37–58. [CrossRef] Mathematics 2023, 11, 899 20 of 20
- Ruder, S. An Overview of Gradient Descent Optimization Algorithms. arXiv 2016, arXiv:1609.04747.
Paper not yet in RePEc: Add citation now
- Salinas, D.; Flunkert, V.; Gasthaus, J. DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks. Int. J. Forecast. 2020, 36, 1181–1191. [CrossRef]
Paper not yet in RePEc: Add citation now
- Sanger, T.D. Optimal Unsupervised Learning in a Single-Layer Linear Feedforward Neural Network. Neural Netw. 1989, 2, 459–473. [CrossRef]
Paper not yet in RePEc: Add citation now
- Sheikholeslami, G.; Chatterjee, S.; Zhang, A. WaveCluster: A Wavelet-Based Clustering Approach for Spatial Data in Very Large Databases. VLDB J. 2000, 8, 289–304. [CrossRef]
Paper not yet in RePEc: Add citation now
- Sherstinsky, A. Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network. Phys. D Nonlinear Phenom. 2020, 404, 132306. [CrossRef]
Paper not yet in RePEc: Add citation now
- Shewchuk, J.R. An Introduction to the Conjugate Gradient Method without the Agonizing Pain; Carnegie-Mellon University, Department of Computer Science Pittsburgh: Pittsburgh, PA, USA, 1994.
Paper not yet in RePEc: Add citation now
- Silva, A.J.; Cortez, P.; Pereira, C.; Pilastri, A. Business Analytics in Industry 4.0: A Systematic Review. Expert Syst. 2021, 38, e12741. [CrossRef]
Paper not yet in RePEc: Add citation now
- Sornalakshmi, M.; Balamurali, S.; Venkatesulu, M.; Krishnan, M.N.; Ramasamy, L.K.; Kadry, S.; Lim, S. An Efficient Apriori Algorithm for Frequent Pattern Mining Using Mapreduce in Healthcare Data. Bull. Electr. Eng. Inform. 2021, 10, 390–403. [CrossRef] Mathematics 2023, 11, 899 17 of 20
Paper not yet in RePEc: Add citation now
- Stadler, J.G.; Donlon, K.; Siewert, J.D.; Franken, T.; Lewis, N.E. Improving the Efficiency and Ease of Healthcare Analysis Through Use of Data Visualization Dashboards. Big Data 2016, 4, 129–135. [CrossRef] [PubMed]
Paper not yet in RePEc: Add citation now
- Stelzer, G.; Rosen, N.; Plaschkes, I.; Zimmerman, S.; Twik, M.; Fishilevich, S.; Stein, T.I.; Nudel, R.; Lieder, I.; Mazor, Y.; et al. The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses. Curr. Protoc. Bioinform. 2016, 54, 1–30. [CrossRef] [PubMed]
Paper not yet in RePEc: Add citation now
- Trkman, P.; McCormack, K.; de Oliveira, M.P.V.; Ladeira, M.B. The Impact of Business Analytics on Supply Chain Performance. Decis. Support Syst. 2010, 49, 318–327. [CrossRef]
Paper not yet in RePEc: Add citation now
Troilo, M.; Bouchet, A.; Urban, T.L.; Sutton, W.A. Perception, Reality, and the Adoption of Business Analytics: Evidence from North American Professional Sport Organizations. Omega 2016, 59, 72–83. [CrossRef]
- Tsamardinos, I.; Brown, L.E.; Aliferis, C.F. The Max-Min Hill-Climbing Bayesian Network Structure Learning Algorithm. Mach. Learn. 2006, 65, 31–78. [CrossRef]
Paper not yet in RePEc: Add citation now
- Uddin, S.; Haque, I.; Lu, H.; Moni, M.A.; Gide, E. Comparative Performance Analysis of K-Nearest Neighbour (KNN) Algorithm and Its Different Variants for Disease Prediction. Sci. Rep. 2022, 12, 6256. [CrossRef] [PubMed]
Paper not yet in RePEc: Add citation now
- van der Togt, J.; Rasmussen, T.H. Toward Evidence-Based HR. JOEPP 2017, 4, 127–132. [CrossRef]
Paper not yet in RePEc: Add citation now
- Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A.N.; Kaiser, Ł.; Polosukhin, I. Attention Is All You Need. Adv. Neural Inf. Process. Syst. 2017, 30. [CrossRef]
Paper not yet in RePEc: Add citation now
- Videla-Cavieres, I.F.; Ríos, S.A. Extending Market Basket Analysis with Graph Mining Techniques: A Real Case. Expert Syst. Appl. 2014, 41, 1928–1936. [CrossRef]
Paper not yet in RePEc: Add citation now
- Vinyals, O.; Fortunato, M.; Jaitly, N. Pointer Networks. In Proceedings of the 28th International Conference on Neural Information Processing Systems, Cambridge, MA, USA, 7 December 2015; Volume 2, pp. 2692–2700.
Paper not yet in RePEc: Add citation now
- Wang, L. Heterogeneous Data and Big Data Analytics. ACIS 2017, 3, 8–15. [CrossRef] Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Paper not yet in RePEc: Add citation now
- Wang, W.; Yang, J.; Muntz, R. STING: A Statistical Information Grid Approach to Spatial Data Mining. Vldb 1997, 97, 186–195.
Paper not yet in RePEc: Add citation now
- Ware, C. Information Visualization: Perception for Design; Morgan Kaufmann: Burlington, MA, USA, 2019; ISBN 0-12-812876-3.
Paper not yet in RePEc: Add citation now
- Wen, R.; Torkkola, K.; Narayanaswamy, B.; Madeka, D. A Multi-Horizon Quantile Recurrent Forecaster. arXiv 2017, arXiv:1711.11053.
Paper not yet in RePEc: Add citation now
- Williams, H.P. Model Building in Mathematical Programming; John Wiley & Sons: Hoboken, NJ, USA, 2013; ISBN 1-118-50618-9.
Paper not yet in RePEc: Add citation now
- Wolpert, D.H. Stacked Generalization. Neural Netw. 1992, 5, 241–259. [CrossRef]
Paper not yet in RePEc: Add citation now
- Wu, P.-J.; Huang, P.-C. Business Analytics for Systematically Investigating Sustainable Food Supply Chains. J. Clean. Prod. 2018, 203, 968–976. [CrossRef]
Paper not yet in RePEc: Add citation now
- Yang, X.Y.; Liu, Z.; Fu, Y. MapReduce as a Programming Model for Association Rules Algorithm on Hadoop. In Proceedings of the 3rd International Conference on Information Sciences and Interaction Sciences, Chengdu, China, 23–25 June 2010; pp. 99–102.
Paper not yet in RePEc: Add citation now
- Zerveas, G.; Jayaraman, S.; Patel, D.; Bhamidipaty, A.; Eickhoff, C. A Transformer-Based Framework for Multivariate Time Series Representation Learning. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, Singapore, 14–18 August 2021; pp. 2114–2124. Mathematics 2023, 11, 899 19 of 20
Paper not yet in RePEc: Add citation now
- Zhang, T.; Ramakrishnan, R.; Livny, M. BIRCH: An Efficient Data Clustering Method for Very Large Databases. ACM Sigmod Rec. 1996, 25, 103–114. [CrossRef]
Paper not yet in RePEc: Add citation now
- Zhao, R.; Liu, Y.; Zhang, N.; Huang, T. An Optimization Model for Green Supply Chain Management by Using a Big Data Analytic Approach. J. Clean. Prod. 2017, 142, 1085–1097. [CrossRef]
Paper not yet in RePEc: Add citation now
- Zhou, H.; Zhang, S.; Peng, J.; Zhang, S.; Li, J.; Xiong, H.; Zhang, W. Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting. AAAI Conf. Artif. Intell. 2021, 35, 11106–11115. [CrossRef]
Paper not yet in RePEc: Add citation now
- Zhou, L.; Zhong, Z.; Chang, J.; Li, J.; Huang, J.Z.; Feng, S. Balanced Parallel FP-Growth with MapReduce. In Proceedings of the 2010 IEEE Youth Conference on Information, Computing and Telecommunications, Beijing, China, 28–30 November 2010; pp. 243–246.
Paper not yet in RePEc: Add citation now
Zhou, W.; Chen, M.; Yang, Z.; Song, X. Real Estate Risk Measurement and Early Warning Based on PSO-SVM. Socio-Econ. Plan. Sci. 2021, 77, 101001. [CrossRef]