State-of-the-Art and Challenges in Timeline Summarization Katja Markert 0 Institute of Computational Linguistics University of Heidelberg Heidelberg , Germany

Timeline Summarization (TLS) creates an overview of long-running events via dated daily summaries for the most important dates and is essential to keep track of a ood of information on, for example, crises data. TLS di ers from standard single and multi-document summarization in the importance of date selection, interdependencies between summaries of di erent dates, the lack of large-scale human training data and a very low compression rate, i.e very short summaries in comparison to the number of corpus documents. In this talk, I will discuss the impact these properties have on (i) optimization algorithms and objective functions for timeline summarization algorithms (ii) evaluation of timeline summarization outputs and (iii) the dependence of TLS on information retrieval components.