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- W1517760109 abstract "Predicting and improving the performance of sales representatives to boost the marketing of various products is very important for distribution companies or agencies. This paper is an attempt to use the data mining processes and techniques, particularly clustering and classification, for evaluating sales representatives’ data and studying the main attributes that may affect their performance in marketing distribution companies to help enhance the quality of the marketing system. The first phase of the work involves collection and preparation of data for all the testing areas according to the target value. The second phase plays a vital role in clustering using the K-means method to group the unknown clusters. The third phase involves applying the classification techniques namely tree induction of decision tree methods based on information theory and Gini index to evaluate the performance of the sales representatives." @default.
- W1517760109 created "2016-06-24" @default.
- W1517760109 creator A5083623299 @default.
- W1517760109 date "2010-07-22" @default.
- W1517760109 modified "2023-09-23" @default.
- W1517760109 title "Improving Performance of Sales Representatives Through Data Mining Techniques" @default.
- W1517760109 hasPublicationYear "2010" @default.
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