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  • 學位論文

網際網路購物代理人之設計與建構

The Design and Implementation of a Shopping Agent on the Internet

指導教授 : 李錫捷
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摘要


由於網際網路的便利性,因此發展出各式各樣的電子商務活動及內容提供網站(ICP)。使用者只要透過搜尋引擎就可以找到許多相關的商品、服務或內容資訊。然而對於搜尋引擎所查詢到的資料廣度及深度都巳經有非常不錯的結果,但是面對網頁內容不一,而且又不是以標準的格式來呈現,也造成資訊蒐集及整合工作上會有相當大的負擔。 因此本研究希望運用代理人技術,並透過學習式機制,能夠從文件之中擷取出有用的部份,以創造出資訊本身的價值。其中主要結合智慧搜尋、資訊過濾、資訊擷取、規則學習的方法,以提升資訊擷取的品質,達到資訊蒐集目的。最後根據研究的內容,建置成購物代理人系統,並以網路上的購物資訊作為資料來源,讓使用者能多樣化的查詢特定商品資訊並提供個人化資訊整合服務。同時以評估系統對於資料的收集能力和擷取的正確率,來作為驗證本研究可行性和實用性之所在。

並列摘要


In recent years, due to the emerging technologies on the Internet, various Internet services are available including e-commerce activities and Internet content providers. It is convenient to find the desired product information from the Internet by utilizing various search engines available. However, there exist no standards for the content providers in presenting their valuable data in a structured way. Therefore, to effectively extract specific information and collect data from the semi-structured Internet documents has become a problem. In this study, a shopping agent is designed and implemented. It is an intelligent agent that does information extraction and has a global supervised-learning mechanism. In other words, this agent learns every time it provides its service to a user. The knowledge is accumulated during the runtime of the system. Whatever it learned from one user is reusable globally by others that request the similar services from the same agent. This is a very important concept here since it learns once and works forever unless the reference template is modified. Various experiments are conducted which tried to simulate searching for some merchandise. The experimental results are promising and the system has demonstrated its practicability as a great shopping assistant.

參考文獻


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