Biomedical question-focused multi-document summarization: ILSP and AUEB at BioASQ3

Abstract. Question answering systems aim to find answers to natural language questions by searching in document collections (e.g., reposi-tories of scientific articles or the entire Web) and/or structured data (e.g., databases, ontologies). Strictly speaking, the answer to a question might sometimes be simply ‘yes ’ or ‘no’, a named entity, or a set of named entities. In practice, however, a more elaborate answer is often also needed, ideally a summary of the most important information from relevant documents and structured data. In this paper, we focus on gen-erating summaries from documents that are known to be relevant to par-ticular questions. We describe the joint participation of AUEB and ILSP in the corresponding subtask of the bioasq3 competition, where partic-ipants produce multi-document summaries of given biomedical articles that are relevant to English questions prepared by biomedical experts