Supporting web content quality: formalizing metadata concepts for the web domain
Dawn G. Gregg, Kenneth Goul · 2000
Poor web data quality can have many costs for the typical enterprise. This is true for web based data as well as for traditional data sources. This applied research investigates the use of distributed artificial intelligence approaches for supporting web content quality. A series of prototyping/validation tasks will be conducted to evolve web-based systems that can be used to maintain web content quality. First, a meta-data protocol that provides improved access to DSS will be developed and validated. Next, a formal web data model will be developed. This model will offer a framework for defining web object dependencies and representations. These two concepts are then combined to develop a prototype Web-Quality protocol. This protocol will facilitate the maintenance of web-based content by allowing meta-data about web pages and the relationship between web pages to be distributed with web pages. Intelligent agents are used to translate this meta-data into appropriate action.