Multi-Document Summarization by Capturing the Information Users are Interested in

This paper proposes a method for automatically 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 input documents to automatically extract the most relevant sentences and build the summaries. In order to evaluate the performance of our approach, we conduct two types of evaluation. On the one hand, we use ROUGE to assess the information contained in our summaries against existing human written summaries, whereas on the other hand, we carry out a human readability evaluation. Our results indicate that our approach achieves high performance both in ROUGE and manual evaluation.