BibSonomyburst/bibtex/191c2d0e9a6625bc92333180b41b9c579BibSonomy RSS feed for /bibtex/191c2d0e9a6625bc92333180b41b9c5792012-02-17T15:54:59+01:00http://www.bibsonomy.org/bibtex/26e72a18ed2b4c950397ad9dc44ec59e7/cscholzcscholz2010-05-31T14:24:49+02:00clustering kdd networks social text <span class="authorEditorList"><a href="/author/Chang">Jonathan Chang</a>, <a href="/author/Boyd-Graber">Jordan L. Boyd-Graber</a>, and <a href="/author/Blei">David M. Blei</a> </span><em>KDD, </em><em>page 169-178. </em>(<em>2009</em>)Mon May 31 14:24:49 CEST 2010KDDDBLP:conf/kdd/2009169-178Connections between the lines: augmenting social networks with text2009clustering kdd networks social text http://www.bibsonomy.org/bibtex/25ddcf06e18cb1e3ba0232be987ecd953/lee_pecklee_peck2010-01-14T19:59:52+01:0009 Chang extraction network social text <span class="authorEditorList"><a href="/author/Chang">Jonathan Chang</a>, <a href="/author/Boyd-Graber">Jordan Boyd-Graber</a>, and <a href="/author/Blei">David M. Blei</a> </span><em>KDD &#039;09: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, </em><em>page 169--178. </em><em>New York, NY, USA, </em><em>ACM, </em>(<em>2009</em>)Thu Jan 14 19:59:52 CET 2010New York, NY, USAKDD '09: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining169--178Connections between the lines: augmenting social networks with text200909 Chang extraction network social text Network data is ubiquitous, encoding collections of relationships between entities such as people, places, genes, or corporations. While many resources for networks of interesting entities are emerging, most of these can only annotate connections in a limited fashion. Although relationships between entities are rich, it is impractical to manually devise complete characterizations of these relationships for every pair of entities on large, real-world corpora. In this paper we present a novel probabilistic topic model to analyze text corpora and infer descriptions of its entities and of relationships between those entities. We develop variational methods for performing approximate inference on our model and demonstrate that our model can be practically deployed on large corpora such as Wikipedia. We show qualitatively and quantitatively that our model can construct and annotate graphs of relationships and make useful predictions.Connections between the lineshttp://www.bibsonomy.org/bibtex/2fe07f0fc596eecc140f471f8e38ceffa/dblpdblp2009-07-02T00:00:00+02:00dblp <span class="authorEditorList"><a href="/author/Chang">Jonathan Chang</a>, <a href="/author/Boyd-Graber">Jordan L. Boyd-Graber</a>, and <a href="/author/Blei">David M. Blei</a> </span><em>KDD, </em><em>page 169-178. </em><em>ACM, </em>(<em>2009</em>)Thu Jul 02 00:00:00 CEST 2009KDDconf/kdd/2009169-178Connections between the lines: augmenting social networks with text.2009dblp dblp