| Abstract: | The automatic generation of summaries using cases (GARUCAS) environment was designed as an intelligent system to help one learn to summarize narrative texts by means of examples within a case‐based reasoning (CBR) approach. Each example, modeled as a case, contains a conceptual representation of the initial textual state, the different steps of the summarization method, and the representation of the final textual state obtained. The CBR approach allows the environment to summarize new texts in order to produce new text summarization examples with respect to some predefined educational objectives. Within GARUCAS, this approach is used at two levels: an event level (EL) in order to identify essential elements of a story, and the clause level (CL) to make the summary more readable. The purpose of this article is to describe the GARUCAS environment and the model used to build story summarization examples and summarize new texts. This model is based on important psycholinguistic work concerning event and narrative structures and text revision rules. An experiment was conducted with 12 short stories. The GARUCAS environment can classify the stories according to their structure analogy and reuse the summarization method of the most similar text. Such an approach can be reused for any kind of texts or summary types. © 2003 Wiley Periodicals, Inc. |
