Several studies have focused on problems related to data mining techniques, including several applications of these techniques in the e-commerce setting. In this work, we describe how data mining technology can be effectively applied in an e-commerce environment, delivering significant benefits to the business analyst. We propose a framework that takes the results of the data mining process as input, and converts these results into actionable knowledge, by enriching them with information that can be readily interpreted by the business analyst. The framework can accommodate various data mining algorithms, and provides a customizable user interface. We experimentally evaluate the proposed approach by using a real-world case study that demonstrates the added benefit of the proposed method. The same study validates the claim that the produced results represent actionable knowledge that can help the business analyst improve the business performance, since it significantly reduces the time needed for data analysis, which results in substantial financial savings.
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Titolo: | A Knowledge Mining Framework for Business Analysts | |
Autori: | Palpanas, Themistoklis | |
Autori Unitn: | ||
Titolo del periodico: | THE DATA BASE FOR ADVANCES IN INFORMATION SYSTEMS | |
Anno di pubblicazione: | 2012 | |
Numero e parte del fascicolo: | 1 | |
Codice identificativo Scopus: | 2-s2.0-84858242969 | |
Codice identificativo WOS: | WOS:000301547900003 | |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1145/2139011.2139015 | |
Handle: | http://hdl.handle.net/11572/88869 | |
Appare nelle tipologie: | 03.1 Articolo su rivista (Journal article) |