近年來，隨著網際網路技術迅速的發展造成網路使用率的普及日益上升，對於網站是否能針對使用者提供適合的資訊以及縮短回應時間的技術越來越究。為了達到這個目的，必須追蹤並且分析使用者使用網路的行為模式，藉此改善網頁架構，提供更好的客制化服務。本研究應用Petri-net技術來預測使用者的瀏覽路徑行為，了解網頁的結構與內容是否真正符合使用者的需求，以改善網頁結構的設計或內容。本研究中，以教育部大學課程網網站為例，使用Petri-net掌握網路使用者的動作，藉此提供使用者的路徑資料庫，使系統能正確的判斷使用者瀏覽路徑，並且應用此技術建立的預測模組改善網頁位置，使系統能預先做處理，縮短回應時間。我們希望藉由分析網路使用者歷史的瀏覽行為紀錄，建立預測模型來預測其他使用者未來可能瀏覽的網頁，並預先存取準備提供給使用者。研究中發現以下結果：
1. 使用Petri-net技術真實掌握網路使用者的動態行為，藉此提供使用者的路徑資料庫。
2. 使用轉換控制矩陣方法來建構規則表和預測模型，藉此改善網頁的架構。
研究發現使用此技術建立的預測模組，能更準確的預測使用者未來的瀏覽路 徑，並且改善網頁位置架構，增進使用者瀏覽網頁效能。

Information of network grows up fast, and there is an important thing to provide user a tool for searching information quickly. To track and analyze user behavior of network is a helpful work for achiving above purpose. We apply Petri-net approach which is used to accurately capture user behavior of network traffic, and the proposed prediction model is constructed by log database. This research is used Petri-net method to grasp the user behavior accurately, and it offers path of user behavior. And we use converted weight matrix method to construct rule table and prediction model, and it has flexibility to make management and access of the database more convenient. The experimental results showed that improve site of website and predict path of user behavior efficiently. This research is found:
1. Petri-net to grasp the user behavior accurately and it offers database of user behavior.
2. Converted weight matrix method to construct rule table and prediction model. This method can keep flexibility to system, and make management and access of the database more convenient.

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