This is an abstractive summarization demo program. It was mainly used to summarize opinions, but since it does not rely on any domain information, it can be used to summarize any highly redundant text.
Text Mining Recommendation Systems/ Collaborative Filtering, Structure Web Graph Page Rank/Spam Social Networking, Data Structures Bloom Filters ... Stanford University course; resources, links, more.
C. Zhai, A. Velivelli, and B. Yu. Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, page 743--748. New York, NY, USA, ACM, (2004)
P. Kluegl, M. Atzmueller, and F. Puppe. Proc. LWA 2009, Knowledge Discovery and Machine Learning Track, Darmstadt, Germany, University of Darmstadt, (2009)
P. Kluegl, M. Atzmueller, and F. Puppe. Proc. LWA 2009, Knowledge Discovery and Machine Learning Track, Darmstadt, Germany, University of Darmstadt, (2009)