臺灣博碩士論文加值系統

以螞蟻系統探索大型資料庫, 可以用來發覺相關性的模型, 許多公司以發覺關聯性規則的方式, 來了解不同產品之間的關聯性, 以更進一步的改善客戶服務並擴大市場. 近來, 有許多的演算法提出, 分別對值化及量化資料加以演算, 而螞蟻系統則可以同時考慮這兩種資料型態, 以有效率並可靠的方式演算出結果,以提供決策者有效的決策支援. 在本篇論文中, 我們應用並提出相關性質與分析螞蟻系統建立關連項目及其強度, 進而了解其正確性,穩定性與複雜度, 同時以一示例說明之.

Mining association rules is to find relations among large amount of data so that the pattern of the dataset can be discovered. Many companies use association rules to find the relations among different items to improve their service quality of customers or enlarge their marketplace. Recently, many algorithms have been developed that only consider either non-quantitative data or quantitative data. However, in reality, most data we collected are mixed in types. Since Ant System allows to consider both of data types and has advantages of being efficient in filtering the unobvious association rules to reduce the unnecessary outputs and ease of making judgment to improve the performance, therefore, in this study, we adopted the technique and concept of Ant System to develop association rules. The developed algorithm is supported by theoretical evidence, and comparative studies are provided for evaluation.

摘 要 ......................i
ABSTRACT...................ii
ACKNOWLEDGEMENT ...........iii
CONTENTS...................iv
TABLE AND FIGURE CAPTIONS ...v
LIST OF NOTATIONS..........vi
Chapter 1 INTRODUCTION ......1
Chapter 2 LITERATURE REVIEW..6
2-1. Association Rules ......6
2-2. An Ant System ..........9
Chapter 3 THE PROPOSED METHOD FOR DISCOVERING ASSOCIATION RULES...................13
3-1. Properties of the Association Rules ........13
3-2. The Algorithm...............................14
3-3. Evaluation and Discussion ..................19
IV. NUMERICAL ILLUSTRATION......................24
4-1. Numerical Example......................24
4-2. Efficiency and Reliability.............26
4-2-1. Accuracy of Proposed Method.............26
4-2-2. Stability of Proposed Method.............28
V. SUMMERY AND CONCLUSION......................31
REFERENCES...............................32
APPENDIX........................................34
Appendix A. Unsupervised Result of Proposed Ant System
...............................34
Appendix B. Proposed Ant System Program...35

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