This paper describes a program which revises a draft text by aggregating together descriptions of discourse entities, in addition to deleting extraneous information. In contrast to knowledgerich sentence aggregation approaches explored in the past, this approach exploits statistical parsing and robust coreference detection. In an evaluation involving revision of topic-related summaries using informativeness measures from the TIPSTER SUMMAC evaluation, the results show gains in informativeness without compromising readability.

No abstract

No abstract

This paper presents a method for constructive induction, in which new attributes are constructed as various functions of original attributes. Such a method is called data-driven constructive induction, because new attributes are derived from an analysis of the data (examples) rather than the generated rules. Attribute construction and rule generation is repeated until a termination condition, such as the satisfaction of a rule quality measure, is met. The first step of this method, the generation of new attributes has been implemented in AQl7-PRE. Initial experiments with AQl7-PRE have shown that it leads to an improvement of the learned rules both in terms of their simplicity as well as accuracy on testing examples.

No abstract