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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.<\/jats:p>\n          <jats:p>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.<\/jats:p>","DOI":"10.1145\/2139011.2139015","type":"journal-article","created":{"date-parts":[[2012,2,14]],"date-time":"2012-02-14T13:21:07Z","timestamp":1329225667000},"page":"46-60","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["A knowledge mining framework for business analysts"],"prefix":"10.1145","volume":"43","author":[{"given":"Themis","family":"Palpanas","sequence":"first","affiliation":[{"name":"University of Trento, Trento, Italy"}]}],"member":"320","published-online":{"date-parts":[[2012,2]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Cross Industry Standard Process for Data Mining. http:\/\/www.crisp-dm.org\/ 2011.  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