A knowledge-based approach to merging information
There is an increasing need for technology for merging semi-structured information (such as structured reports) from heterogeneous sources. For this, we advocate a knowledge-based approach when the information to be merged incorporates diverse, and potentially complex, conflicts (inconsistencies). In this paper, we contrast the goals of knowledge-based merging with other technologies such as semantic web technologies, information mediators, and database integration systems. We then explain how a system for knowledge-based merging can be constructed for a given application. To support the use of a knowledgebase, we use fusion rules to manage the semi-structured information that is input for merging. Fusion rules are a form of scripting language that defines how structured reports should be merged. The antecedent of a fusion rule is a call to investigate the information in the structured reports and the background knowledge, and the consequent of a fusion rule is a formula specifying an action to be undertaken to form a merged report. Fusion rules are not necessarily a definitive specification of how the input can be merged. They can be used by the user to explore different ways that the input can be merged. However, if the user has sufficient confidence in the output from a set of fusion rules, they can be regarded as a definitive specification for merging, and furthermore, they can then be treated as a form of meta-knowledge that gives the provenance of the merged reports. The integrated usage of fusion rules with a knowledgebase offers a practical and valuable technology for merging conflicting information.
semi-structured information conflicting information information integration knowledge fusion knowledge merging inconsistent information