Byrne, E.L.; (2005) The expectation violation analysis framework: the analysis and evaluation of interesting news by means of inconsistency with expectations. Doctoral thesis , University of London.

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Abstract

Large volumes of news are available around the clock and around the world. It is increasingly difficult to sort interesting from uninteresting news. Information filtering and retrieval have addressed this problem by comparing lexical information in documents with a query or profile of user's interests. However, this approach does little to address the fact that the most interesting news is usually that which is unexpected. This thesis presents a framework that addresses this problem by reasoning about the information in reports, comparing it with the general knowledge of background information and expectations. This framework makes it possible to identify and rank unexpected, and therefore interesting, news. The Expectation Violation Analysis (EVA) framework presented here draws reasoned conclusions as to why the information in a report is or is not interesting. The EVA framework contains a set of background knowledge and a set of expectations which represent the usual state of the world. When a report contains information that contradicts this knowledge and these expectations then that report contains information that is of interest. This thesis demonstrates that the EVA framework supports the development of a system that rates news reports for interest together and explains why the report was considered unexpected. This thesis also shows that the set of all expectations is very large. It is demonstrated that the strength of expectations is related to the implication order of the antecedents and consequents of those expectations. A method for generating expectations based on news reports and background knowledge is presented, as is empirical work that indicates the approach is plausible. Also presented is a novel extension to the event calculus that permits reasoning about missing states. These extensions support the development of expectations and background knowledge that make it possible to reason about time.

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