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3.3 SUDY APPROACH AND METHODOLOGY As an empirical study based strongly in survey application data over user experiences and perceptions, a data mining approach will be applied to collect, store, qualify and evaluate data about the SE ranking factors. Data mining technology allows to extract implicit information from where people do not know in advance but potentially can be transformed in useful information. As referred in Introduction chapter, SE is some software category which collects data about websites. The related collected data is indexed and stored on a database. Furthermore, a production of software has a lot of affinity with data mining application techniques. In both scenarios, data analysis must be done to allow acquisition and automation of a new knowledge. Here, business domain may be understood to mean information that would facilitate new knowledge comprehension, in other words, it is not just documenting some existent knowledge being applied in the field of business, but also a process of knowledge discovery (Liu, Zhon & Zong, 2010). 3.3.1 Study Configuration To achieve the targeted objectives using data mining techniques, four major phases (Figure 2) will be assigned to the method of this project, as follows: Figure 2 - Cross Industry Standard Process for Data Mining Source: CRISP-DM Consortium, Aug 2006. 7PDF Image | Prova de trabalho de projeto conducent
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