Quality-Driven Information Filtering in the Context of Web-Based Information Systems

Abstract

Web-based information systems provide access to information originating from multiple information providers inside the company, from partner organizations, and from the public Web. The quality of provided information may vary as information providers have different levels of knowledge, different views of the world, and different intentions. Thus before information is used to accomplish a specific task, its quality should be assessed according to task-specific criteria. The goal of the thesis is to develop and evaluate a quality-driven information filtering framework which supports information consumers in their decision whether to accept or reject information. The main objective of the framework is to allow information consumers to apply a wide range of different subjective filtering policies. In order to facilitate the information consumers understanding of filtering decisions, the framework can generate explanations why information satisfies a specific policy. The framework is integrated into a web browser and is applied within a financial information integration scenario.