A dynamic understanding of customer behavior processes based on clustering and sequence mining
Expert Systems with ApplicationsPublished 5 February 2014
Alex Seret, Seppe K. L. M. vanden Broucke, Bart Baesens, Jan Vanthienen
Citations30
SJR quartileQ1
SJR score1.85
SNIP2.55
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
A novel approach towards enabling the exploratory understanding of the dynamics inherent in the capture of customers’ data at different points in time is outlined, and how behavior trajectories can help to explain consumer decisions and to improve business processes that are influenced by customer actions is shown.
Abstract
In this paper, a novel approach towards enabling the exploratory understanding of the dynamics inherent in the capture of customers’ data at different points in time is outlined. The proposed methodology combines state-of-art data mining clustering techniques with a tuned sequence mining method to discover prominent customer behavior trajectories in data bases, which — when combined — represent the “behavior process” as it is followed by particular groups of customers. The framework is applied to a real-life case of an event organizer; it is shown how behavior trajectories can help to explain consumer decisions and to improve business processes that are influenced by customer actions.
Keywords
Computer ScienceBusiness, Management and AccountingPhysics and Astronomy
Encyclopedia of Statistics in Behavioral SciencePrincipal Component Analysis
14,549 Citations2005Ian T. Jolliffe
Springer series in information sciencesSelf-Organizing Maps
10,377 Citations1997Teuvo Kohonen
The mathematical preliminaries, background, basic ideas, and implications of the Self-Organising Map algorithm are expounded in a manner which is accessible without prior expert knowledge.
IEEE Transactions on Pattern Analysis and Machine IntelligenceA Cluster Separation Measure
8,543 Citations1979David L. Davies, Donald W. Bouldin
A measure is presented which indicates the similarity of clusters which are assumed to have a data density which is a decreasing function of distance from a vector characteristic of the cluster which can be used to infer the appropriateness of data partitions.
Lecture notes in computer scienceMining sequential patterns: Generalizations and performance improvements
2,686 Citations1996Ramakrishnan Srikant, Rakesh Agrawal
This work adds time constraints that specify a minimum and/or maximum time period between adjacent elements in a pattern, and relax the restriction that the items in an element of a sequential pattern must come from the same transaction.
IEEE Transactions on Knowledge and Data EngineeringWorkflow mining: discovering process models from event logs
2,180 Citations2004Wil M. P. van der Aalst, Ton Weijters +1 more
A new algorithm is presented to extract a process model from a so-called "workflow log" containing information about the workflow process as it is actually being executed and represent it in terms of a Petri net.
ACM Transactions on Software Engineering and MethodologyDiscovering models of software processes from event-based data
874 Citations1998Jonathan Cook, Alexander L. Wolf
This article describes a Markov method that was developed specifically for process discovery, as well as describe two additional methods that were adopted from other domains and augmented for this purposes.
Lecture notes in computer scienceMining process models from workflow logs
786 Citations1998Rakesh Agrawal, Dimitrios Gunopulos +1 more
This work presents an approach for a system that constructs process models from logs of past, unstructured executions of the given process, and presents results from applying the algorithm to synthetic data sets as well as process logs obtained from an IBM Flowmark installation.
Lecture notes in computer scienceDecision Mining in ProM
284 Citations2006A. Rozinat, Wil M. P. van der Aalst
This paper describes how machine learning techniques can be leveraged for decision mining, and presents a Decision Miner implemented within the ProM framework.
World DevelopmentFinancial Efficiency and Social Impact of Microfinance Institutions Using Self-Organizing Maps
143 Citations2013Philippe Louis, Alex Seret +1 more
Decision Support SystemsWeb page clustering using a self-organizing map of user navigation patterns
136 Citations2003Kate Smith‐Miles, Alan Ng
LOGSOM is developed, a system that utilizes Kohonen's self-organizing map to organize web pages into a two-dimensional map that provides a meaningful navigation tool that is easily incorporated with web browsers and serves as a visual analysis tool for webmasters to better understand the characteristics and navigation behaviors of web users visiting their pages.
Acquire (CQUniversity)Design and Application of Hybrid Intelligent Systems
106 Citations2003Ajith Abraham, Mario Köppen +1 more
This volume focuses on the recent research developments on intelligent systems in a hybrid environment and its applications in business systems, image processing, Internet modeling, control/automation and data mining.
Expert Systems with ApplicationsClustering and visualization of bankruptcy trajectory using self-organizing map
94 Citations2012Ning Chen, Bernardete Ribeiro +2 more
This study uses self-organizing map (SOM) to analyze and visualize the financial situation of companies over several years through a two-step clustering process and demonstrates the promising functionality of SOM for bankruptcy trajectory clustering and visualization.
GeoInformaticaVisualizing Demographic Trajectories with Self-Organizing Maps
89 Citations2005André Skupin, Ron Hagelman
This paper proposes to add another perspective to the visualization of temporal change, by linking multi-temporal observations to a geometric configuration that is not based on geographic space, but on a spatialized representation of n-dimensional attribute space.
Decision Support SystemsA service oriented architecture to provide data mining services for non-expert data miners
77 Citations2012Marta Zorrilla, Diego García‐Saiz
A data mining service addressed to non-expert data miners which can be delivered as Software-as-a-Service, whose main advantage is that by simply indicating where the data file is, the service itself is able to perform all the process.
Applied Soft ComputingDynamic rough clustering and its applications
52 Citations2012Georg Peters, Richard W. Weber +1 more
R rough clustering offers strong tools to detect changing data structures and has been applied to synthetic as well as to real-world data sets where it provides new insights regarding the underlying dynamic phenomena.
European Journal of Operational ResearchA new SOM-based method for profile generation: Theory and an application in direct marketing
29 Citations2012Alex Seret, Thomas Verbraken +2 more
A SOM-based profile generator is presented, consisting of a generic method leading to value-adding and business-oriented profiles for targeting individuals with predefined characteristics and the proposed method is applied in detail to a concrete case study from the concert industry.
Lecture notes in computer scienceCountry Corruption Analysis with Self Organizing Maps and Support Vector Machines
21 Citations2006Johan Huysmans, David Martens +3 more
Data mining techniques are applied onto a cross-country database linking macro-economical variables to perceived levels of corruption, and projection of the forecasts onto a self organizing map allows a detailed comparison between the different models' behavior.
Applied Soft ComputingA new knowledge-based constrained clustering approach: Theory and application in direct marketing
20 Citations2014Alex Seret, Thomas Verbraken +1 more
An approach giving the possibility to incorporate business knowledge in order to guide the clustering algorithm is presented, and the fact that an intuitive a priori prioritization of the variables might exist is presented and applied in a direct marketing context using recent data.
Environmental Policy and GovernancePublic Governance, Human Capital and Environmental Outcomes: an Analysis Based on Self‐Organizing Maps
8 Citations2012Vittorio Carlei, Alessandro Marra +1 more
Constructing Markov Models for Reliability Assessment with Self-Organizing Maps
6 Citations2006Maurício Sperandio, Jorge Coelho
This paper shows how a pattern recognition method, the self-organizing maps (SOM) or the Kohonen's neural network, can be used to construct a Markov model by means of state assignment to a process.
Hybrid retention strategy formulation in telecom based on k-means clustering analysis
6 Citations2011Xiaoyan Li, Yang Huang +2 more
An idea of formulating hybrid strategy to retain valuable customers using clustering technology is proposed and the dataset of a Chinese telecom company is used as an illustrative case study to demonstrate the feasibility and rationality of the method.
Hybrid Intelligent SystemsImproving risk grouping rules for prostate cancer patients using self-organising maps
6 Citations2003Daniel Schwartz, Kate Smith‐Miles +3 more
This work aims to improve accuracy by identifying inconsistencies utilising self-organising maps as a data visualisation tool for classification of prostate cancer patients into risk groups using data from the Alfred Hospital.
Lecture notes in business information processingAn Exploratory Approach for Understanding Customer Behavior Processes Based on Clustering and Sequence Mining
1 Citations2014Alex Seret, Seppe K. L. M. vanden Broucke +2 more
A novel approach towards enabling the exploratory understanding of the dynamics inherent in the capture of customers’ data at different points in time is outlined and it is shown how behavior trajectories can help to explain consumer decisions and to improve business processes that are influenced by customer actions.