TY - CONF A1 - Riedhammer, Korbinian A1 - Favre, Benoit A1 - Hakkani-Tür, Dilek T1 - A Keyphrase Based Approach to Interactive Meeting Summarization T2 - 2008 IEEE Workshop on Spoken Language Technologies (SLT), Goa, India, December 2008. N2 - Rooted in multi-document summarization, maximum marginal relevance (MMR) is a widely used algorithm for meeting summarization (MS). A major problem in extractive MS using MMR is finding a proper query: the centroid based query which is commonly used in the absence of a manually specified query, can not significantly outperform a simple baseline system. We introduce a simple yet robust algorithm to automatically extract keyphrases (KP) from a meeting which can then be used as a query in the MMR algorithm. We show that the KP based system significantly outperforms both baseline and centroid based systems. As human refined KPs show even better summarization performance, we outline how to integrate the KP approach into a graphical user interface allowing interactive summarization to match the user's needs in terms of summary length and topic focus. KW - meeting summarization KW - keyword generation KW - user interaction Y1 - 2018 UR - https://opus4.kobv.de/opus4-rosenheim/frontdoor/index/index/docId/287 SP - 153 EP - 156 ER -