Hasso Plattner Institut
Imprint   Data Privacy

Ralf Krestel

You are here:   Home > Publications > Conference Papers > WI 15

WI 15

Online Temporal Summarization of News Events


Nowadays, an ever increasing number of news articles is published on a daily basis. Especially after notable national and international events or disasters, news coverage rises tremendously. Temporal summarization is an approach to automatically summarize such information in a timely manner. Summaries are created incrementally with progressing time, as soon as new information is available. Given a user-defined query, we designed a temporal summarizer based on probabilistic language models and entity recognition. First, all relevant documents and sentences are extracted from a stream of news documents using BM25 scoring. Second, a general query language model is created which is used to detect typical sentences respective to the query with Kullback-Leibler divergence. Based on the retrieval result, this query model is extended over time by terms appearing frequently during the particular event. Our system is evaluated with a document corpus including test data provided by the Text Retrieval Conference (TREC).

Full Paper


Conference Homepage

WI 2015

BibTex Entry


Watch our new MOOC in German about hate and fake in the Internet ("Trolle, Hass und Fake-News: Wie können wir das Internet retten?") on openHPI (link).

New Photos

I added some photos from my trip to Hildesheim.

Powered by CMSimple| Template: ge-webdesign.de| Login