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Building and Querying Large Modelbases

Authors: Tuzhilin, Alexander
Liu, Bing
Hu, Jie
Issue Date: 2005
Publisher: Stern School of Business, New York University
Series/Report no.: CeDER-05-16
Abstract: Model building is one of the most important objectives of data mining and data analysis. As many data mining applications, such as personalization, bioinformatics and some large enterprise-wide business applications, become increasingly complex and require a very large number of models, it is becoming progressively more difficult for data analysts to built and to manage a large number of models in these applications on their own. Therefore, development of software tools helping data analysts in these tasks is becoming a pressing issue. This paper presents a model management system supporting various types of data mining models. It describes how to build and populate large heterogeneous modelbases. It also presents a query language for querying these modelbases and examines performance results for some of the queries.
Appears in Collections:CeDER Working Papers
IOMS: Information Systems Working Papers

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