高效益量化項目集探勘(High Utility Quantitative Itemset Mining)為一門新興的研究議題，其考慮項目的效益屬性(例如：數量、重要度等)，從資料庫中找出高效益且帶有數量資訊的項目集。在商業應用中，該技術可從顧客的交易紀錄中，找出「購買M到N個A商品的顧客也會同時購買P到Q個B商品」這種高獲利的消費行為。雖然此技術能廣泛地應用於許多領域中，然而，現今方法儲存結構牽涉龐大計算量，且往往在探勘過程中產生過多候選項目集，因而導致探勘工作效率不佳、使用者不易分析結果等問題。有鑑於此，本論文提出一個名為HUQI-Miner (High Utility Quantitative Itemsets Miner)的演算法，能夠更有效率地從資料庫中挖掘高效益量化項目集(High Utility Quantitative Itemset，簡稱HUQI)。為了提供使用者精簡的探勘結果並提升探勘工作之效能，本論文率先提出兩種新型的HUQI，分別稱為精簡型及彙整型HUQI。透過所提出的推論方法，精簡型HUQI可推導出符合某些條件的HUQI，而彙整型HUQI則提供使用者效益值較高的HUQI之彙整。本論文利用真實及模擬資料驗證所提方法之執行效率。實驗結果顯示所提出之新創方法所挖掘的型樣不僅精簡又有意義，且其執行速度及記憶體使用量大幅優於目前最佳的演算法。

High utility quantitative itemsets (abbreviated as HUQIs) mining is a novel research topic in data mining field, which considers the concept of utility like quantity and profit to find high utility itemsets carrying information about quantity. In market analysis, it could reveal to decision-makers that shopping behavior could bring high profit to the company. For example, the customers who purchase M to N units of a product A are likely to purchase P to Q units of a product B. However, existing algorithms involve high computational cost and traditional HUQI mining may produce too many itemsets during the mining process, causing performance problems and making results hard to be utilized by users. In view of this, this thesis proposes a novel algorithm named HUQI-Miner (High Utility Quantitative Itemsets Miner) for efficiently mining HUQIs in databases. Moreover, to efficiently present users concise mining results, this thesis proposes two new types of HUQIs, named concise HUQIs and summarized HUQIs, respectively. Concise HUQIs can be used to infer the HUQIs satisfying certain constrains, while summarized HUQIs provide users a summarization about certain HUQIs. Experimental results on both real and synthetic datasets show that the numbers of concise and summarized HUQIs can be several orders of magnitudes smaller than that of HUQIs. Moreover, HUQI-Miner outperforms the state-of-the-art algorithms in terms of both execution time and memory usage.

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