Can intelligent systems be devised to create concise, fluent, and accurate summaries from vast amounts of data? Researchers have strived to achieve this goal in the past fifty years, starting from the seminal work of Luhn (1958) on automatic text summarization. Existing research includes the development of extractive and abstractive summarization technologies, evaluation metrics (e.g., ROUGE and Pyramid), as well as the construction of benchmark datasets and resources (e.g., annual competitions such as DUC (2001-2007), TAC (2008-2011), and TREC (2014-2016 on Microblog/Temporal Summarization)).
The goal for this workshop is to provide a research forum for cross-fertilization of ideas. We seek to bring together researchers from a diverse range of fields (e.g., summarization, visualization, language generation, cognitive and psycholinguistics) for discussion on key issues related to automatic summarization. This includes discussion on novel paradigms/frameworks, shared tasks of interest, information integration and presentation, applied research and applications, and possible future research foci. The workshop will pave the way towards building a cohesive research community, accelerating knowledge diffusion, developing new tools, datasets and resources that are in line with the needs of academia, industry, and government.