Using data mining methods to build customer profiles

Gediminas Adomavicius; Alexander Tuzhilin

doi:10.1109/2.901170

Using data mining methods to build customer profiles

Gediminas Adomavicius, Alexander Tuzhilin

Information and Decision Sciences

Research output: Contribution to journal › Article › peer-review

191 Scopus citations

Abstract

An approach was developed that uses information from customers' transactional histories to construct individual profiles containing facts about the customer and rules describing that customer's behavior. A method was also established for validating customer's profiles to separate 'good' rules from 'bad'. The profile construction and validation methods were implemented using the 1:1Pro system.

Original language	English (US)
Pages (from-to)	74-81
Number of pages	8
Journal	Computer
Volume	34
Issue number	2
DOIs	https://doi.org/10.1109/2.901170
State	Published - Feb 2001

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10.1109/2.901170

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abstract = "An approach was developed that uses information from customers' transactional histories to construct individual profiles containing facts about the customer and rules describing that customer's behavior. A method was also established for validating customer's profiles to separate 'good' rules from 'bad'. The profile construction and validation methods were implemented using the 1:1Pro system.",

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Using data mining methods to build customer profiles

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