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Data Mining   Term Paper ID:43989 Click to get this paper

Essay Subject: Considers Oracle Database Mining and how mining can be used to perform a market ...... More...

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Paper Abstract: Considers Oracle Database Mining and how mining can be used to perform a market basket analysis. Paper Introduction: Database Mining Database mining is more than performing a query on a database it isthe process-usually automated-of finding heretofore hidden patterns andtrends in the vast amounts of data collected by organizations Chapple Used effectively data mining can help companies gain a competitiveby yielding critical insight into the market Traditional data mining products are external to the database andrequire extensive extraction and transformation tools to perform theirtasks Oracle has taken the radical step of integrating its data miningproduct into the database itself so Text of the Paper: The entire text of the paper is shown below. However, the text is somewhat scrambled. We want to give you as much information as we possibly can about our papers and essays, but we cannot give them away for free. In the text below you will find that while disordered, many of the phrases are essentially intact. From this text you will be able to get a solid sense of the writing style, the concepts addressed, and the sources used in the research paper. Database Mining Database mining is more than performing a query on a database; it isthe process-usually automated-of finding heretofore hidden patterns andtrends in the vast amounts of data collected by organizations (Chapple,2 9). About.com. Oracle has taken the radical step of integrating its data miningproduct into the database itself so that there is no need for the separateextraction and transformation process when using the Oracle Data Mining(ODM) product ("FAQ," 2 9). Unsupervised learning algorithmssupported by ODM include: clustering (hierarchical k-means and orthogonalpartitioning clustering), associations (apriori), feature creation (non-negative matrix factorization), and anomaly detection (support vectormachine). Retrieved 24 June 2 9: .Market basket analysis. The most criticalstep is in building the association rules, and in determining the item set(the items that are purchased). Oracle Corporation. Traditional data mining products are external to the database andrequire extensive extraction and transformation tools to perform theirtasks. With data mining techniques, more subtle relationships can bedetermined with higher probabilities for support (the likelihood that theantecedent condition will occur) and greater confidence levels (theprobability that the follow-on purchase will occur). Data mining. Market basket analysis builds on the concept that consumers whopurchase a particular group of items are more likely to purchase anothergroup of items, as well. One of thecriticisms of market basket analysis is that many of the rules uncoveredare already obvious to experts; thus most supermarkets are laid out insimilar fashion regardless of which company owns them. University of Oregon. Retrieved 24 June 2 9: .Oracle Data Mining Frequently Asked Questions (FAQ). (2 9). Retrieved 24 June 2 9: . (2 9). Market basket analysis provides the analytical power to identifyrelationships among purchases that was previously unavailable. Albion Research. (2 6). Over the years,managers have learned which items customer purchase together and they placethose items together ("Market Basket," 2 9). (2 9). Data mining techniques: Market basket analysis and association rules. Used effectively, data mining can help companies gain a competitiveby yielding critical insight into the market. From those calculations, "actionable"rules can be determined based on the support and confidence levels (Pardoe,2 6). ReferencesChapple, M. Once the item set is determined to aspecific level of detail, probabilities of specific items and combinationsof items selected can be calculated. The ODM product supports supervised and unsupervised data miningalgorithms. Supported supervised learning algorithms include:classification (decision tree, naïve Bayes, adaptive Bayes networks andsupport vector machine), regression (support vector machine) and attributeimportance (minimum description length). Retrieved 24 June 2 9: <>.Pardoe, I. Thus a consumer who purchases hot dog buns,ketchup and hot dogs may be more likely to purchase some type of potatochip than other consumers ("Market Basket," 2 9). If this paper is not what you are looking for, you can search again: Search for: or Click here to request an essay written just for you.