Decision Support and Business Intelligence Systems (8th Edition)

By Efraim Turban, Jay E. Aronson, Ting-Peng Liang, Ramesh Sharda. 2006

784 citations recorded by the source corpus.

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Citations in the corpus

Opening black box Data Mining models using Sensitivity Analysis (2011, background): “Data Mining (DM) enables the extraction of knowledge from such databases to the domain user or decision maker [1][2].”
The application of data mining techniques in financial fraud detection: A classification framework and an academic review of literature (2011, methodology): “[73] define datamining as a process that uses statistical, mathematical, artificial intelligence, and machinelearning techniques to extract and identify useful information and subsequently gain knowledge from a large database.”
Business intelligence in banking: A literature analysis from 2002 to 2013 using text mining and latent Dirichlet allocation (2015, methodology): “Business intelligence (BI) is an umbrella term that includes architectures, tools, databases, applications and methodologies with the goal of analyzing data in order to support decisions of business managers (Turban et al., 2011).”
Critical success factors for a customer relationship management strategy (2007, methodology): “On the other hand one of the main problems companies have encountered when attempting to set their presence on Internet is that many of their processes are not yet automated, and in many cases, are not well deWned [30].”
Application of data mining techniques in customer relationship management: A literature review and classification (2009, methodology): “…technique can perform one or more of the following types of data modelling: The above seven models cover the generally mentioned data mining models in various articles (Ahmed, 2004; Carrier & Povel , 2003; Mitra, Pal, & Mitra, 2002; Shaw, Subramaniam, Tan, & Welge, 2001; Turban et al., 2007).”
Predicting social media performance metrics and evaluation of the impact on brand building: A data mining approach (2016, background): “Data mining enables to identify coherent patterns of information from where to extract useful knowledge (Turban et al., 2011).”
Towards business intelligence systems success: Effects of maturity and culture on analytical decision making (2012, background): “In a decision-support context, business intelligence systems (BIS) have emerged as a technological solution offering data integration and analytical capabilities to provide stakeholders at various organizational levels with valuable information for their decision-making [76].”
Fashion retailing – past, present and future (2014, background): “E-commerce applications expanded rapidly due to the developments of technical innovations [183].”
A Review of Financial Accounting Fraud Detection based on Data Mining Techniques (2012, unknown): “Data mining is also define as ―a process that uses statistical, mathematical, artificial intelligence and machine learning techniques to extract and identify useful information and subsequently gaining knowledge from a large database‖ [14, 15].”
Using sensitivity analysis and visualization techniques to open black box data mining models (2013, methodology): “Five SA methods (three of which are purely new) and four measures of input importance (one novel) are presented.”