隨著網路上資訊爆炸的問題,人們需要一個有效的方法去管理資訊,藉由語意標語言如全球資訊網聯盟(W3C)的資源描述語言(Resource Description Language)可達到資訊的管理。語意網擴展目前的網站結構,在資訊方面給予意義上明確的定義,並且使得人和電腦可以共同合作處理資訊。在這篇論文中,我們設計並實作一個可以管理語意網資料摘要層的架構。這個架構包含三個部分:前端、知識庫和後端。前端部分由一些服務介面所組成,提供使用者存取資料內容,包含概念式搜尋與語意的瀏覽的服務。知識庫是一個以ontology當作骨架schema的知識系統。系統後端提供從內容提供者蒐集資料摘要。這個系統實作在框架系統並結合物件導向的設計方法在網站的設計。我們已經測試這樣的系統在科學網站,我們為科學類的網站蒐集資訊摘要,並建立入口網站。我們測量使用框架系統和傳統的邏輯程式系統存取知識庫時的效能差異。實驗的結果顯示使用框架系統比使用傳統的邏輯程式得到更好的效能。
With the problem of information explosion on the web, people need an efficient way to manage the information by marking it up with a semantic markup language, such as the Resource Description Language of W3C. The Semantic Web is an extension of the current Web where information is given well-defined meaning, better, enabling computers and people to process in cooperation. In this thesis we design and implement an architecture that is able to manage the metadata layer of the Semantic Web. The architecture consists of three parts: front end, knowledge warehouse and backend. The front end consists of service interfaces for user to access the content, including conceptual search and semantic navigation. The knowledge warehouse is a knowledge-based system built upon the schema of ontology. The back end provides functions of metadata collection from content providers. The architecture is implemented upon a frame-based system together with objected-oriented programming on the web. We have tested the resulting system as the ontology-based portal for collecting metadata from scientific web sites. We measure the performance between using frame-based system and logic programming system to access the knowledge warehouse. The experimental result shows that the former approach performs better that the other.