QuOTeS: Query-Oriented Technical Summarization
Juan Ramirez-Orta Eduardo Xamena Ana Maguitman Axel J. Soto Flavia P. Zanoto Evangelos Milios
Abstract. When writing an academic paper, researchers often spend
considerable time reviewing and summarizing papers to extract relevant
citations and data to compose the Introduction and Related Work sections. To
address this problem, we propose QuOTeS, an interactive system designed to
retrieve sentences related to a summary of the research from a collection of
potential references and hence assist in the composition of new papers. QuOTeS
integrates techniques from Query-Focused Extractive Summarization and
High-Recall Information Retrieval to provide Interactive Query-Focused
Summarization of scientific documents. To measure the performance of our
system, we carried out a comprehensive user study where participants uploaded
papers related to their research and evaluated the system in terms of its
usability and the quality of the summaries it produces. The results show that
QuOTeS provides a positive user experience and consistently provides
query-focused summaries that are relevant, concise, and complete. We share the
code of our system and the novel Query-Focused Summarization dataset collected
during our experiments at https://github.com/jarobyte91/quotes.