Applying Association Rule on Data Analysis — A Study for Information Industry
| Autor: | Hsiung, Ping-Ning, 熊萍妮 |
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| Rok vydání: | 2003 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 91 The 21-century is a tough age for enterprises. The problems they face include: the pressure of competitive globalization, short product life cycle, quick response from high quality of client asked and widely impact of digital technology. To maintain competitive, enterprises have to plan strategies aggressively to satisfy the client requirements. They have to invest enormously in the field of R&D technology, try to improve the process of manufacturing and logistic, and seek the way to break through communication barriers among hierarchic organizations. The hope is to earn the most profitable feedback in the near future. One way to achieve these goals is to use data mining analysis. Therefore, how to apply the advanced data mining analysis techniques in databases is very important. By applying data mining, marketing-driven and R&D related knowledge can be obtained. Data mining also helps develop new products to satisfy customers and improve manufacturing process and cut cost. As an important knowledge representation in data mining, frequent itemsets show up numerous product combinations revealing customers’ preferences. Enterprises can take actions based on these analysis reports to lower down cost, increase profits and market share. This thesis studies the daily operational database of a local company. The frequent itemset mining technique is then applied to analyze the sales patterns of the company. The results show that the frequent itemset mining technique can help enterprises improve their business processes. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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