%0 Book Section %1 lessmann08classification %A Lessmann, Stefan %A Voß, Stefan %B Intelligent Decision Support %D 2008 %E Bortfeldt, Andreas %E Homberger, Jörg %E Kopfer, Herbert %E Pankratz, Giselher %E Strangmeier, Reinhard %I Gabler %K applications crm datamining machine-learning %P 231-253 %R 10.1007/978-3-8349-9777-7_14 %T Supervised Classification for Decision Support in Customer Relationship Management %U http://dx.doi.org/10.1007/978-3-8349-9777-7_14 %X Supervised classification embraces theories and algorithms for disclosing patterns within large, heterogeneous data streams. Several empirical experiments in various domains including medical diagnosis, drug design, document and image classification as well as text recognition have proven its effectiveness to solve complex forecasting and identification tasks. This paper considers applications of classification within the scope of customer relationship management (CRM). Representative operational planning tasks are reviewed to describe the potential and limitations of classification analysis. To that end, a survey of the relevant literature is given to summarize the body of knowledge in each field and identify similarities across applications. The discussion provides a general understanding of technical and managerial challenges encountered in typical CRM applications and indicates promising areas for future research. %@ 978-3-8349-9777-7

@incollection{lessmann08classification, abstract = {Supervised classification embraces theories and algorithms for disclosing patterns within large, heterogeneous data streams. Several empirical experiments in various domains including medical diagnosis, drug design, document and image classification as well as text recognition have proven its effectiveness to solve complex forecasting and identification tasks. This paper considers applications of classification within the scope of customer relationship management (CRM). Representative operational planning tasks are reviewed to describe the potential and limitations of classification analysis. To that end, a survey of the relevant literature is given to summarize the body of knowledge in each field and identify similarities across applications. The discussion provides a general understanding of technical and managerial challenges encountered in typical CRM applications and indicates promising areas for future research.}, added-at = {2010-09-16T13:51:11.000+0200}, affiliation = {University of Hamburg Institute of Information Systems Von-Melle-Park 5 D-20146 Hamburg}, author = {Lessmann, Stefan and Voß, Stefan}, biburl = {https://www.bibsonomy.org/bibtex/280ac4360e2bdaa34f75873a68bf085c9/sb3000}, booktitle = {Intelligent Decision Support}, description = {SpringerLink - Abstract}, doi = {10.1007/978-3-8349-9777-7_14}, editor = {Bortfeldt, Andreas and Homberger, Jörg and Kopfer, Herbert and Pankratz, Giselher and Strangmeier, Reinhard}, interhash = {03be096a976aaf28b22419df127a37fb}, intrahash = {80ac4360e2bdaa34f75873a68bf085c9}, isbn = {978-3-8349-9777-7}, keyword = {Economics/Management Science}, keywords = {applications crm datamining machine-learning}, pages = {231-253}, publisher = {Gabler}, timestamp = {2010-09-16T13:51:11.000+0200}, title = {Supervised Classification for Decision Support in Customer Relationship Management}, url = {http://dx.doi.org/10.1007/978-3-8349-9777-7_14}, year = 2008 }