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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/7125


    Title: 應用隨機過程時間派翠網路來強化網頁使用模式探勘
    Other Titles: Enhance Web Usage Mining by Using Stochastic Timed Petri Nets
    Authors: 陳伯榮
    Contributors: 淡江大學資訊工程研究所
    Keywords: 網頁探勘;網頁使用者習性探勘;隨機過程時間派翠網路;連續馬可夫關聯模式;Web Mining;Web Usage Mining;Stochastic Timed Petri Nets;continuous Markov Chain
    Date: 2004
    Issue Date: 2009-03-16 15:38:24 (UTC+8)
    Abstract: 網頁探勘通常被分為:網頁內容探勘、網頁架構探勘及網頁使用者習性探勘等三個 子領域。其中的網頁使用者習性探勘在近年來特別受到研究者的重視。但是Robert Cooley 卻也提到說:網頁使用者習性探勘之所以未能獲得較完美的成果,主要是由於設 計者在探勘的過程未能充分瞭解網頁內容及網頁架構所致。 我們將運用大家所熟知的隨機過程時間派翠網路來分析使用者的使用習性;在這篇 計劃中,我們將先介紹隨機過程時間派翠網路的永不變特性、可到達性及連續馬可夫關 聯模式。接著我們將介紹如何將這三種工具應用於網頁使用者習性探勘中的資料前置處 理及模式發掘階段。 我們計劃探討: (一)利用隨機過程時間派翠網路來建構網頁結構。 (二)利用隨機過程時間派翠網路永不變結構特性和可到達行為特性來協助資料 前置處理。 (三)利用使用者使用網頁資訊來觸發隨機過程時間派翠網路網頁結構模型以協 助完成模式發掘。 (四)解出隨機過程時間派翠網路的相對連續馬可夫關聯模式來進一步分析出有 用的資訊。Web Mining can be divided into three sub-fields, namely content mining, structure mining and usage mining. The research of web mining and especially of web usage mining is receiving increasing attention in recent years. Cooley points out that without good understanding of the content and structure of a web site, web usage mining process can』t complete. The well-known Stochastic Timed Petri Nets (STPN) is introduced to analyze the web usage qualitatively and quantitatively. In this proposal, we first introduce three important analysis tools in STPN, called invariants, reachability, and relative continuous Markov Chain. Then we describe how the three tools can be applied to enhance the web usage mining process in preprocessing and pattern discovery phase. We plan to study how to: [1] construct web structure by using STPN, [2] utilize invariants and reachability properties to enhance the web usage mining process in preprocessing phase, [3] enhance pattern discovery phase, by firing the STPN model using preprocessed click-stream data, [4] and solve the relative continuous Markov Chain model to derive useful information.
    Appears in Collections:[資訊工程學系暨研究所] 研究報告

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