http://netvouz.com/mcswell/tag/computational?feed=rss&pg=3 mcswell's bookmarks tagged "computational" on Netvouz http://www.amazon.com/exec/obidos/tg/detail/-/0520229967/qid=1063301984/sr=1-1/ref=sr_1_1/102-1817203-2546518?v=glance&s=books Computational Linguistics > Lexicography mcswell Thu, 18 Nov 2004 15:10:41 GMT http://www.linguistics.ucla.edu/people/hayes/index.htm Computational Linguistics > People mcswell Thu, 18 Nov 2004 15:10:41 GMT http://www.cse.ogi.edu/ Computational Linguistics > Speech Recognition mcswell Thu, 18 Nov 2004 15:10:41 GMT http://www.ccl.kuleuven.ac.be/ Computational Linguistics mcswell Thu, 18 Nov 2004 15:10:40 GMT http://www.limsi.fr/Individu/jacquemi/ Computational Linguistics > People mcswell Thu, 18 Nov 2004 15:10:41 GMT http://nlp.stanford.edu/~manning/papers/ Computational Linguistics > People mcswell Thu, 18 Nov 2004 15:10:41 GMT http://www.clres.com/ The primary mission of CL Research is to investigate the role of computational lexicons in natural language processing applications. The results of our research is incorporated in the Knowledge Management System (KMS) (for which we are now seeking beta-testers), which is a unified platform for * parsing and analyzing text (from most formats, including Word, PDF, XML, and web pages), * answering free-form natural language questions, * summarizing one or more documents, generally or topic-based, * extracting information, * exploring document contents, and * dynamically creating ontological representations of document contents. Ken Litkowski is the webmaster and author of most (all?) their publications. Located in Maryland. Computational Linguistics > Lexicography mcswell Wed, 20 Feb 2008 17:48:37 GMT http://www.umiacs.umd.edu/research/CLIP/index.htm Computational Linguistics and Information Processing Organizations > U Md mcswell Mon, 29 Sep 2008 12:40:21 GMT http://teach-computers.org/kcvc05.html Computational Linguistics > Wikification mcswell Tue, 29 Mar 2005 14:30:55 GMT http://www.sepln.org/revistaSEPLN/revista/33/33-Pag155.pdf Abstract: In this work three different statistical language identification methods are compared, and a detailed study of the influence on those systems of some basic parameters is performed. The analyzed parameters are the size of the train set, the amount of text that we want to classify and the languages the system is able to distinguish (it will be studied not only the influence of the number of languages but also the influence of which are the considered languages). Computational Linguistics > Language ID mcswell Fri, 24 Feb 2006 21:18:03 GMT