由於電子商務的發展，以往傳統的交易平台也由電話、傳真、書面資料，進展到網際網路。在後端交易資料庫中資料中，隱藏了不易發現的知識或訊息；而這些資料中所隱藏的趨勢或模式，可協助商業的應用上。資料的挖掘在商業市場的應用上有其重要性，其中挖掘的技術更是重要，只要善用其結果將有助於企業取得競爭上的優勢。關聯規則係在網際探勘中的資料挖掘的技術之一，其主要是找出資料庫某些資料項目間彼此的關聯性。由於關聯法則的表現是相當明確，而且易懂，因此被大量廣泛的運用在各種不同的領域上。關聯法則不只找出物件的因果關係，其結果更可做為預測之依據。
本研究旨在以霍普菲爾類神經網路(Hopfield Neural Network)解決關聯規則挖掘找出高頻項目演算法的問題。本文以台北科技大學圖書館學生圖書借閱紀錄為研究對象。藉此可使圖書館員找出本校學生借閱書籍的偏好與借閱情況，並可為學生在將來添購他們喜歡閱讀種類的書籍，滿足學生需求，同時可使整體圖書館借閱率提高，也可提供圖書館作為其他決策之參考。依本研究結果顯示：應用科學類與社會科學類的書籍具有高度的關聯規則存在。

The new Transaction Platform, Internet, has replaced telephone, fax and paper works because of the development of Electronic Commerce. Whether the message or any undiscovered knowledge is hided in the transaction database or not, the trends or model hided in data can provide application in business. The Data Mining is very useful in business market, as for the technique of Data Mining is more important. As long as people could make a good use of the technique, the technique would help to create a better situation. Association Rule is very important for the technique of Data Mining on web. People could use Association Rule to find the relatinship between some itemsets in databases. The theory of Association Rules is easy and understandable; therefore, it is used extensively in many fields. People could not only use Association Rule to find out the relationship between cause and effect, but also use it to do some forecasts.
The substance of the study is to find out how Associatin Rule solves the frequency itemset problem by using Hopfield Neural Network. In this study, student loan registration records from National Taipei University of Technology library are the main reference. The library staff could find out student’s preference and the rates of books loan registration records. Then, the library staff can purchase new books to satisfy students’ needs; furthermore, the result of Association Rule could help to improve the rates of loan books. Moreover, the analysis results may become useful reference for liberary staff. In the study, the result shows that there are strict rules between the books of applied science and society science.

摘要iii
Abstractiv
誌謝v
目次vi
表目錄viii
圖目錄ix
第一章 緒論1
1.1 研究動機1
1.2 研究目的2
1.3 研究流程3
第二章 文獻探討5
2.1 網際探勘5
2.2 網際探勘技術9
2.3 關聯法則13
2.4 類神經網路與資料挖掘38
第三章 ARM霍普菲爾-坦克網路模式46
3.1 平行挖掘關聯規則46
3.2 霍普菲爾-坦克類神經網路47
3.3 ARM霍普菲爾-坦克類神經網路模式55
第四章 實驗結果與分析60
4.1 圖書館資料庫結構情境60
4.2 資料轉換61
4.3 關聯規則評估項目65
4.4 參數最佳化66
4.5 實驗結果比較與分析79
第五章 結論與建議93
5.1 結論93
5.2 未來研究建議94
參考文獻95

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