Design and Implementation of an Adaptive Web Warehousing System

在網際網路成為新一代媒體的今日，如何從龐大的瀏覽記錄挖掘出有價值的
使用者行為，便成為所有網路服務者亟需面對的課題。本研究之第二階段，承接
前一階段的研究成果，建置Web 環境應用所需的資料倉儲，包含資料轉換程序
與資料倉儲系統架設，最後整合資訊勘測的諸項技術，包括相關性、分類與瀏覽
路徑等，以尋求隱含於大量使用者資訊中的行為模式，此勘測結果可提供使用者
個人化的資訊服務，亦可回授至本倉儲系統以動態的調校資料儲存結構，維持系
統最佳化，此一具可適性之特點將特別適用於目前線上的Web 環境。具體而言，
整合以上各項技術成為一適合Web 的應用環境且具線上分析勘測功能之資料倉
儲系統是本計畫的首要目標，因此，我們針對資料倉儲系統之需求而研發資料擷
取、儲存與勘測機制及其系統架構。

As Internet technologies develop rapidly these years, more and more people are
attracted by various web applications. How to collect and save the user data
efficiently and to find the valuable knowledge from the huge data have become
important topics. In this project, the high-efficiency data collection mechanism and
corresponding data processing steps for web environments are first being developed.
Second, the OLAP techniques are utilized to build a Web warehousing system.
Additionally, data mining capabilities, i.e., association, classification and traversal
pattern, are devised to explore the user behaviors hidden in large amount of user data.
The mining results offer personal services for Web users, and can be feedback for our
system to trigger the dynamic adjustment of storage architectures for optimizing the
system. This adaptive characteristic is most suitable for online Web systems. Hence,
integrating the technologies mentioned above to build an adaptive web warehousing
system with the OLAM functionality is our objective of this project.