Semantic Web-based Information Process and Personalization Applying to Enterprise Information Portal Resources Integration

• Main Authors: LIN,HSIU-TE, 林修德
• Other Authors: Chen, Tsung Teng
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/21812941451354504210

碩士 === 國立臺北大學 === 資訊管理研究所 === 96 === Enterprise Information Portal (EIP) uses web technology to integrate different sources of information systems into a single user interface and makes enterprise employees and clients perform information management more easily. Although EIP puts diverse systems into homogeneous EIP modules, the contents of the modules are still isolated. For the integration of the contents and mining, exploring the contents of EIP, a further research is still needed. Since the Pioneer of World Wide Web, Tim Berners-Lee, introduced the concept of Semantic Web, the research of web resources automation processing and integration has been the trend. Additionally, it brings new hopes to the research of integration of EIP modules. At the present stage, the research of semantic web mostly focuses on knowledge modeling and internal annotation of the web resources. It utilizes Bottom up method to build a semantic web knowledge base in order to provide an automation mechanism of web resource integration. The research of EIP contents integration primarily focuses on generating ontology natively. In other words, it provides ontology for the semantic web agents originally. If there is no ontology schema of the EIP, the semantic web agents could not exploit the EIP contents. Therefore, we present an external annotation-based EIP resource integration and personalization framework to help the EIP, which lacks a self-description schema, benefit from semantic web technology. The framework uses structure-driven web crawler to retrieve the contents for each EIP module. Subsequently, it applies slot-tree filling algorithm to annotate the documents in a way to make them meaningful. At the same time, it transforms the meaningful documents into RDF instances and combines them with specific personal ontology. Consequently, this framework builds a semantic web knowledge base of the EIP in which it allows users to query and obtain integration information. Nonetheless, the integration information inevitably loses its context, and it leads users not to be able to find the original information comes from quickly. We utilize Cluster Map to display the integration information and the original context in an attempt to solve this problem. Finally, through a case study and simulation, the framework of this research successfully facilitates enterprise employees to work more efficiently. To provide the automation processing of web resources, web contents integration and reuse of ontology is the main tasks and challenges of semantic web technology. This research provides a suggestion solution with the theory and practice of the semantic web technology.