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Text-to-text generation applications (e.g., summarization) could also benefit from an automatic paragaraph segementation mechanism which indicates topic shifts and provides visual targets to the reader. We present a paragraph segmentation model which exploits a variety of knowledge sources (including textual cues, syntactic and discourse-related information) and evaluate its performance in different languages and domains. Our experiments demonstrate that the proposed approach significantly outperforms our baselines and in many cases comes to within a few percent of human performance. Finally, we integrate our method with a single document summarizer and show that it is useful for structuring the output of automatically generated text.<\/jats:p>","DOI":"10.1145\/1149290.1151098","type":"journal-article","created":{"date-parts":[[2006,10,18]],"date-time":"2006-10-18T18:11:32Z","timestamp":1161195092000},"page":"1-35","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Broad coverage paragraph segmentation across languages and domains"],"prefix":"10.1145","volume":"3","author":[{"given":"Caroline","family":"Sporleder","sequence":"first","affiliation":[{"name":"Tilburg University, LE Tilburg, The Netherlands"}]},{"given":"Mirella","family":"Lapata","sequence":"additional","affiliation":[{"name":"University of Edinburgh, Edinburgh, UK"}]}],"member":"320","published-online":{"date-parts":[[2006,7]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proceedings of the ACL Workshop on Intelligent Scalable Text Summarization","author":"Barzilay R.","unstructured":"Barzilay , R. and Elhadad , M . 1997. 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