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The true lift model

Victor S. Y. Lo
2002 SIGKDD Explorations  
In database marketing, data mining has been used extensively to find the optimal customer targets so as to maximize return on investment.  ...  In particular, using marketing campaign data, models are typically developed to identify characteristics of customers who are most likely to respond.  ...  CONCLUSION We have presented a novel approach to response modeling in database marketing.  ... 
doi:10.1145/772862.772872 fatcat:qbb6tojq5nbjrmyqfvmc5ss2iq

A Data Mining-Based Response Model for Target Selection in Direct Marketing

Eniafe Festus Ayetiran, Adesesan Barnabas Adeyemo
2012 International Journal of Information Technology and Computer Science  
Using historical purchase data, a predictive response model with data mining techniques was developed to predict a probability that a customer in Ebedi Microfinance bank will respond to a promotion or  ...  To achieve this purpose, a predictive response model using customers' historical purchase data was built with data mining techniques.  ...  Knowledge discovery in databases is the process of identifying valid, novel, potentially useful, and ultimately understandable patterns/models in data.  ... 
doi:10.5815/ijitcs.2012.01.02 fatcat:4qje6775efgdhgm6mc2uk3baq4

Response Modeling in Direct Marketing [chapter]

Sadaf Hossein Javaheri, Mohammad Mehdi Sepehri, Babak Teimourpour
2014 Data Mining Applications with R  
In direct marketing, data mining has been used extensively to identify potential customers for a new product (target selection).  ...  Using historical purchase data, a predictive response model with data mining techniques is developed to predict a probability that a customer is going to respond to a promotion or an offer.  ...  The purpose of data mining is to identify valid, novel, useful, and ultimately understandable patterns in data.  ... 
doi:10.1016/b978-0-12-411511-8.00006-2 fatcat:p73qqvzrabgg3c5ay23j4vw6oa

A Stacking Approach to Direct Marketing Response Modeling

Ernest Kangogo Kiprop, George Okeyo, Petronilla Muriithi
2018 Asian Journal of Research in Computer Science  
In this work, we investigate the viability of the stacked generalization approach in predictive modeling of a direct marketing problem.  ...  We will demonstrate a significant improvement in the AUC and lift values when the stacked generalization approach is used viz a viz the single-algorithm approach.  ...  Data mining has been defined as the process of selection, exploration and modeling of large databases in order to discover models and patterns that are unknown apriori [1] .  ... 
doi:10.9734/ajrcos/2018/v1i224726 fatcat:7lwd56bqwnav7faezv5cw5khla

An Application of Association Rule Mining in Total Productive Maintenance Strategy: An Analysis and Modelling in Wooden Door Manufacturing Industry

Taufik Djatna, Imam Muharram Alitu
2015 Procedia Manufacturing  
Through an analysis and modelling of the OEE value obtained from the factory, the formulation of Association Rule Mining (ARM) aims to find a rule that shows the well computed relationship between measurable  ...  This research investigates the answers of these challenges by analysing and modelling the equipment condition and the response of actions required in a wooden door manufacturing industry.  ...  Conclusion and recommendation This paper presents a novel implementation of data mining techniques to solve real industry problem especially in machine maintenance in a wooden door manufacturing industry  ... 
doi:10.1016/j.promfg.2015.11.049 fatcat:uht4rwcdwndz7kvw3pitwbicay

Intelligent data analysis approaches to churn as a business problem: a survey

David L. García, Àngela Nebot, Alfredo Vellido
2016 Knowledge and Information Systems  
In particular, the use of intelligent data analysis, or data mining, for the analysis of market surveyed information can be of great assistance to churn management.  ...  In this context, anticipating the customer's intention to abandon the provider, a phenomenon known as churn, becomes a competitive advantage.  ...  Lima EO (2009) Domain knowledge integration in data mining for churn and customer lifetime value modelling: New approaches and applications.  ... 
doi:10.1007/s10115-016-0995-z fatcat:2k3c3dnh75ggnesqkrif3w6cwm

Bank Deposit Prediction Using Ensemble Learning

Muhammed J. A. Patwary, S. Akter, M. S. Bin Alam, A. N. M. Rezaul Karim
2021 Artificial Intelligence Evolution  
The purpose of this paper is to study the performance of ensemble learning algorithms which is a novel approach to predict whether a new customer will have a term deposit or not.  ...  Due to such economic depression, banks cannot attract a customer's attention. Thus, marketing is preferred to be a handy tool for the banking sector to draw customers' attention for a term deposit.  ...  In bank marketing, various data mining algorithms can be used for classifying as well.  ... 
doi:10.37256/aie.222021880 fatcat:7nasbw4vqbhcpmmpsaqmsgmjmq

An Efficient Data Mining Method for Learning Bayesian Networks Using an Evolutionary Algorithm-Based Hybrid Approach

M.L. Wong, K.S. Leung
2004 IEEE Transactions on Evolutionary Computation  
The approach is applied successfully to handle the business problem of finding response models from direct marketing data. Learning Bayesian networks from data is a difficult problem.  ...  This study proposes a novel data mining approach that employs an evolutionary algorithm to discover knowledge represented in Bayesian networks.  ...  Acknowledgment The authors are grateful to Prof. Xin Yao and anonymous referees for their constructive suggestions for improving the paper.  ... 
doi:10.1109/tevc.2004.830334 fatcat:3uyun7dbqbeuhd4lyu6pcbtqba

The Alzheimer's comorbidity phenome: mining from a large patient database and phenome-driven genetics prediction

Chunlei Zheng, Rong Xu
2018 JAMIA Open  
This exploratory study demonstrated the potential of disease-comorbidities mining from FAERS in AD genetics discovery.  ...  We built a DCN based on indication data from FAERS using association rule mining. DCN was further integrated with PPI network.  ...  Recently, we developed a novel a context-sensitive network (CSN) approach to model the complex, heterogeneous, and contextspecific interactions among tens of thousands of biomedical entities, including  ... 
doi:10.1093/jamiaopen/ooy050 pmid:30944912 pmcid:PMC6434979 fatcat:hcgswvfhzfchze2b7p3tyqlkhi

Data Mining; A Conceptual Overview

Joyce Jackson
2002 Communications of the Association for Information Systems  
Essentially, the two types of data mining approaches differ in whether they seek to build models or to find patterns.  ...  The tutorial also provides a basic understanding of how to plan, evaluate and successfully refine a data mining project, particularly in terms of model building and model evaluation.  ...  Data Mining: A Conceptual Overview by J. Jackson Tao, G. (1999), "KPS A Web Information Mining Algorithm", Computer Networks, (31), 1495-1508.  ... 
doi:10.17705/1cais.00819 fatcat:r32fl7rksrherhx3xpvx7ci37q

Improved response modeling based on clustering, under-sampling, and ensemble

Pilsung Kang, Sungzoon Cho, Douglas L. MacLachlan
2012 Expert systems with applications  
In this paper, we propose a novel data balancing method based on clustering, under-sampling, and ensemble to deal with the class imbalance problem, and thus improve response models.  ...  Endemic in customer data used for response modeling is a class imbalance problem: the proportion of respondents is small relative to non-respondents.  ...  Is he/she going to respond? provided by the Dutch data mining company ''Sentiment Machine Research'' for a data mining competition purpose.  ... 
doi:10.1016/j.eswa.2011.12.028 fatcat:cth7oo2otbap5b7zowunr5ecj4

A Financial Data Mining Model for Extracting Customer Behavior

Mark K.Y. Mak, George T.S. Ho, S.L. Ting
2011 International Journal of Engineering Business Management  
This paper aims at developing an intelligent Financial Data Mining Model (FDMM) for extracting customer behavior in the financial industry, so as to increase the availability of decision support data and  ...  To validate the feasibility of the proposed model, a simple dataset is collected from a financial company in Hong Kong.  ...  Architecture of Financial Data Mining Model (FDMM) In order to gain a better understanding on investors' behavior and achieve higher customer satisfaction, a Financial Data Mining Model (FDMM) is proposed  ... 
doi:10.5772/50937 fatcat:fhg3iigyjffkzgowvljudclkry

Domain driven data mining to improve promotional campaign ROI and select marketing channels

Thomas Piton, Julien Blanchard, Henri Briand, Fabrice Guillet
2009 Proceeding of the 18th ACM conference on Information and knowledge management - CIKM '09  
Data mining methods could be interesting to generate substantial profits for decision makers and to optimize the choice of different marketing activities.  ...  In this paper, we propose an actionable knowledge discovery methodology, for one-to-one marketing, which allows to contact the right customer through the right communication channel.  ...  ACKNOWLEDGMENTS The authors would like to thank Pierrick Richard and Gaëtan Blain (VM Matériaux company) for supporting this work. They also thank Laurent Tessier (KXEN company) for his comments.  ... 
doi:10.1145/1645953.1646088 dblp:conf/cikm/PitonBBG09 fatcat:mmc3xj27rbdvtez7pfkwtuafwi

An Integrated Knowledge Discovery and Data Mining Process Model [chapter]

Sumana Sharma, Kweku-Muata Osei-Bryson
2015 Knowledge Discovery Process and Methods to Enhance Organizational Performance  
Osei-Bryson, you are a true scholar with a gentle soul, and I am so grateful that I had you as my advisor.  ...  I feel extremely fortunate in that I had the opportunity to work with him, and regard the moment when I got introduced to him as the turning point in my academic life.  ...  In developing response models in marketing it is common to divide the population into ten deciles and rank the deciles by lift.  ... 
doi:10.1201/b18231-5 fatcat:cmb5frhjczhcnlmzd5f7u55nvu

A divide-and-conquer strategy using feature relevance and expert knowledge for enhancing a data mining approach to bank telemarketing

Sérgio Moro, Paulo Cortez, Paulo Rita
2017 Expert systems  
in particular in bank marketing.  ...  The inbound telemarketing sub-problem re-evaluation led to a large increase in targeting performance, confirming the benefits of such approach, considering the importance of telemarketing for business,  ...  The usage of a customer database can enhance the process, turning it into database marketing (Tapp, 2008) .  ... 
doi:10.1111/exsy.12253 fatcat:t6jrg62dk5bqbfsu5z4azd3fb4
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