Wed, 20 Aug 2008 22:06:47 BST CiteULike: bkhl library [4 articles] http://www.citeulike.org/user/bkhl CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/bkhl/article/2947678 <i>(2–6 July 1984), pp. 75-78.</i><br /><br />Functional Unification Grammar provides an opportunity to encompass within one formalism and computational system the parts of machine translation systems that have usually been treated separately, notably analysis, transfer, and synthesis. Many of the advantages of this formalism come from the fact that it is monotonic allowing data structures to grow differently as different nondeterministic alternatives in a computation are pursued, but never to be modified in any way. A striking feature of this system is that it is fundamental reversible, allowing α to translate as β only if β could translate as α. Functional Unification Grammar: A Formalism for Machine Translation Martin Kay (2–6 July 1984), pp. 75-78. 2008-07-01T11:21:19-00:00 1984 75 78 Association for Computational Linguistics grammar linguistics http://www.citeulike.org/user/bkhl/article/2947538 <i>(June 2008), pp. 97-105.</i> Competitive Grammar Writing Jason Eisner Noah Smith (June 2008), pp. 97-105. 2008-07-01T10:53:57-00:00 2008 97 105 Association for Computational Linguistics grammar linguistics statistics http://www.citeulike.org/user/bkhl/article/105906 <i>(18 June 1999)</i><br /><br />"Statistical natural-language processing is, in my estimation, one of the most fast-moving and exciting areas of computer science these days. Anyone who wants to learn this field would be well advised to get this book. For that matter, the same goes for anyone who is already in the field. I know that it is going to be one of the most well-thumbed books on my bookshelf." -- Eugene Charniak, Department of Computer Science, Brown University <P>Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications. <P>More on this book Foundations of Statistical Natural Language Processing Christopher Manning Hinrich Schütze (18 June 1999) 2005-02-27T13:16:32-00:00 1999 The MIT Press linguistics statistics http://www.citeulike.org/user/bkhl/article/161657 <i>(15-16 August 1998), pp. 1-8.</i><br /><br />This paper describes a method for asking statistical questions about a large text corpus. We exemplify the method by addressing the question, "What percentage of Federal Register documents are real documents, of possible interest to a text researcher or analyst?" We estimate an answer to this question by evaluating 200 documents selected from a corpus of 45,820 Federal Register documents. Stratified sampling is used to reduce the sampling uncertainty of the estimate from over 3100 documents to fewer than 1000. The stratification is based on observed characteristics of real documents, while the sampling procedure incorporates a Bayesian version of Neyman allocation. A possible application of the method is to establish baseline statistics to estimate recall rates for information retrieval systems. Bayesian Stratified Sampling to Assess Corpus Utility Judit Hochberg Clint Scovel Timothy Thomas Sam Hall (15-16 August 1998), pp. 1-8. 2005-04-15T09:46:15-00:00 1998 1 8 linguistics statistics