Key Element-Context Model: An Approach to Efficient Web Metadata Maintence

• Main Authors: VUONG, Ba-Quy, LIM, Ee Peng, SUN, Aixin, CHANG, Chew-Hung, Chatterjea, Kalyani, GOH, Dion Hoe-Lian, THENG, Yin-Leng, ZHANG, Jun
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2007
• Subjects: Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/1267; http://dx.doi.org/10.1007/978-3-540-74851-9_6
• Institution: Singapore Management University

In this paper, we study the problem of maintaining metadata for open Web content. In digital libraries such as DLESE, NSDL and G-Portal, metadata records are created for some good quality Web content objects so as to make them more accessible. These Web objects are dynamic making it necessary to update their metadata records. As Web metadata maintenance involves manual efforts, we propose to reduce the efforts by introducing the Key element-Context (KeC) model to monitor only those changes made on Web page content regions that concern metadata attributes while ignoring other changes. We also develop evaluation metrics to measure the number of alerts and the amount of efforts in updating Web metadata records. KeC model has been experimented on metadata records defined for Wikipedia articles, and its performance with different settings is reported. The model is implemented in G-Portal as a metadata maintenance module.