5.1 結論
隨著網路服務技術的快速發展，越來越多的服務提供者都提供了相同功能的 服務，為了幫助使用者能夠從這群相同功能的服務當中選出一個好的服務，解決 服務選擇的問題，並且驗證網路服務服務品質的正確性，來過濾掉服務品質不好 的網路服務，本論文提出了一個基於服務品質和協同過濾機制的兩階段網路服務 發現演算法。
在第一階段是利用過往使用者的查詢行為，並且透過協同過濾來滿足使用者 的功能性需求，以及驗證服務品質的正確性，過濾掉不好的網路服務。因此，在 這階段中，本方法不用收集任何使用者對網路服務的評分，避免了惡意使用者或 錯誤評分的問題。第二階段再依據使用者的服務品質需求，來排序第一階段所推 薦的網路服務集合，使得越符合使用者需求的網路服務，排名會再越前面，如此 不僅可以滿足使用者對網路服務的非功能性需求，亦能提升網路服務查詢的精確 率。
最後，在實驗中我們以 Average Precision 為評估指標，並且實作了一雛型系 統稱為 WSDigger，來比較本方法與 QoS Ranking 方法和協同過濾方法的效能。
實驗的結果也指出，本方法的效能可以達到 96%的精確率，其效能是明顯優於其 他兩個方法。
5.2 未來方向
在未來研究方面，由於本論文在查詢網路服務時只有以文字來考量，一開始 是以關鍵字為基礎的查詢方式，之後再利用協同過濾機制來提升精確率。因此，
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在這裡可能可以結合語意(Semantic)的概念，除了能夠更準確的找出使用者有興 趣的網路服務之外，更希望可以建構網路服務的本體論(Ontology)，來描述網路 服務之間的關連性，提供更有效率的網路服務查詢的方法。此外，不管是在 UDDI 中或是使用者所發出的查詢請求中，本論文假設服務品質資訊的單位都是統一的 預設值，但是服務品質的單位在實際上會有多個定義，因此，在未來也希望可以 建構服務品質的本體論，讓不同的服務品質單位之間能夠自動的轉換數值。
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