Scalable Inference of Customer Similarities from Interactions Data using Dirichlet Processes
Under the sociological theory of homophily, people who are similar to one another are more likely to interact with one another. Marketers often have access to data on interactions among customers from which, with homophily as a guiding principle, inferences could be made about the underlying similarities. However, larger networks face a quadratic explosion in the number of potential interactions that need to be modeled. This scalability problem renders probability models of social interactions...[Show more]
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|Source:||Marketing Science: the marketing journal of INFORMS|
|01_Braun_Scalable_Inference_of_Customer_2010.pdf||1.23 MB||Adobe PDF||Request a copy|
|02_Braun_Scalable_Inference_of_Customer_2010.pdf||134.63 kB||Adobe PDF||Request a copy|
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