Laura Plaza

This paper proposes a method for automat-ically generating summaries taking into account the information in which users may be interested. Our approach relies on existing model summaries from tourist sites and captures from them the type of information humans use to describe places around the world. Relational patterns are first extracted and categorized by the type of information they encode. Then, we apply them to the collection of in-put documents to automatically extract the most relevant sentences and build the sum-maries. In order to evaluate the perfor-mance of our approach, we conduct two types of evaluation. On the one hand, we use ROUGE to assess the information con-tained in our summaries against existing human written summaries, whereas on the other hand, we carry out a human readabil-ity evaluation. Our results indicate that our approach achieves high performance both in ROUGE and manual evaluation.