By Héctor Oscar Nigro, Sandra Elizabeth Gonzalez Cisaro, Daniel Hugo Xodo
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Additional info for Date Mining with Ontologies: Implementations, Findings and Frameworks
Sample text
This is a fact that has positive and negative consequences. A disadvantage would be the missing details due to replacing interests by their ancestors. Those details could have been used as direct business act indicators about a product. Thus, a rule which involves deep-level interests can explicitly express a connection between customers and products. Such a rule might connect a specific movie DVD with a demographic group. It is, of course, possible to perform data mining before Raising. Thus, no real loss occurs.
The definition and implementation of Raising are presented in this chapter. Furthermore, the effects caused by Raising are analyzed in detail, showing an improvement of the support and confidence values of useful association rules for marketing purposes. intrOdUCtiOn Marketing has faced new challenges over the past decade. The days of the mass market are definitely over. Consumers now are exposed to numerous cable channels and satellite channels. Many people do not get their information from TV at all, but use Web sites.
For convenience, it is assumed that every interest in the hierarchy is assigned a level L by a revised breadth-first search algorithm, LEVEL- Raising, to Enhance Rule Mining in Web Marketing with the Use of an Ontology BFS(), as described in (Zhou, 2006, pp. 24-25). Then the level function L(T) is defined to return this level as a number. Interests nearer to the root have lower level numbers. The root is by definition at level 0. Lower levels in the diagram correspond to higher level numbers.