International audienceCustomer Relationship Management is an every day task for companies, even the ones dealing with Small Data. We are more interested here by Lead Scoring that refers to the practice of calculating and assigning a score to leads (business contacts or qualified prospects) of the company. In this paper, we present one way of building a Lead scoring model with a Bayesian network using a small amount of data. In addition to its ability of handling uncertainty, Bayesian networks are knowledge representation models that can be built from expert knowledge. In our specific context, we then propose to build our Lead scoring model from expertise and apply usual heuristics to decrease the complexity of our model (parent divorcing, N...
Complex network data problems are increasingly common in many fields of application. Our motivation ...
We focus on purchase incidence modelling for a European direct mail company. Response models based o...
The article proposes a method for producing configurations of values in firms. Values have an impact...
A Bayesian Network is a probabilistic graphical model that represents a set of variables and their p...
AbstractModelling relationships between variables has been a major challenge for statisticians in a ...
Undoubtedly, customer relationship management has gained its importance through the statement that a...
This chapter presents an application of Bayesian network technology in an empirical customer satisfa...
The growing area of Data Mining defines a general framework for the induction of models from databas...
As a compact graphical framework for representation of multivariate probabilitydistributions, Bayesi...
A Bayesian network is a graphical model that encodes probabilistic relationships among variables of ...
A Bayesian network is a widely used probabilistic graphical model with applications in knowledge dis...
We formalise and present an innovative general approach for developing complex system models from su...
Customer data today typically include a large number of customers with disaggregated information abo...
Bayesian Networks (BNs) are popular computer models used to perform reasoning under uncertainty. The...
Probabilistic reasoning, among methodologies used within the domain of artificial intelligence, is r...
Complex network data problems are increasingly common in many fields of application. Our motivation ...
We focus on purchase incidence modelling for a European direct mail company. Response models based o...
The article proposes a method for producing configurations of values in firms. Values have an impact...
A Bayesian Network is a probabilistic graphical model that represents a set of variables and their p...
AbstractModelling relationships between variables has been a major challenge for statisticians in a ...
Undoubtedly, customer relationship management has gained its importance through the statement that a...
This chapter presents an application of Bayesian network technology in an empirical customer satisfa...
The growing area of Data Mining defines a general framework for the induction of models from databas...
As a compact graphical framework for representation of multivariate probabilitydistributions, Bayesi...
A Bayesian network is a graphical model that encodes probabilistic relationships among variables of ...
A Bayesian network is a widely used probabilistic graphical model with applications in knowledge dis...
We formalise and present an innovative general approach for developing complex system models from su...
Customer data today typically include a large number of customers with disaggregated information abo...
Bayesian Networks (BNs) are popular computer models used to perform reasoning under uncertainty. The...
Probabilistic reasoning, among methodologies used within the domain of artificial intelligence, is r...
Complex network data problems are increasingly common in many fields of application. Our motivation ...
We focus on purchase incidence modelling for a European direct mail company. Response models based o...
The article proposes a method for producing configurations of values in firms. Values have an impact...