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<html><head><title>CS674 Project Presentation Schedule</title></head><center><h1>CS674 Project Presentation Schedule</h1></center><body><h2>April 24<sup>th</sup></h2><ol><li><b>Kendra Willson</b><br><i>Thematic roles and NLU</i><br>This paper muses on issues surrounding the adaptation of various linguisticapproaches to argument structure for NLP purposes, with theultimate but oblique goal of shedding light on the age-old question: Arelinguists useless?<p><li><b>Catherine Starkey</b><br><i>A German/English Translator for Simple Sentences</i><br>This project will take as input a series of sentences in English or German and then parse them according to a corresponding set of grammar rules.  Then, using a different set of rules (for the other language), it pieces together the new sentence with words entered in a lexicon.<p><li><b>Lin Hsian Wang</b><br><i>Prepositional Phrase Attachement by Rule-Based Approach</i><br>To solve the prepositional phrase attachment ambiguation using          set of rules generated by Transformation-Based Error-Driven Learning          algorithm.<p><li><b>Mao Yonghong</b><br><i>Part of Speech Tagging Algorithms</i><br>I will compare some part of speech tagging algorithms and try to give somesuggestions.<p><li><b>Eric Scharff</b><br><i>Neural Networks for Part of Speech Disambiguation</i><br><p></ol><h2>April 29<sup>th</sup></h2><ol><li><b>Alfred Hong</b><br><i>Translation of Regular Query Sentences into SQL Queries</i><br> The idea of this stems from the numerous Web forms today         that provide search capability.  Often times, one would         like to have a query interface to a database (relational),         but the search definition parameters are usually restrictive        and "inhuman."  Adding a natural language query capability        to the search function while providing a back-end         conversion to an equivalent SQL query to a database         would makes things more human and natural and hopefully        more powerful.  <p><li><b>Ed Wayt</b><br><i></i><br><p><li><b>Jonathan Decristofaro</b><br><i>Making the Chart Parser Avoid Useless Work</i><br>The bottom-up chart parser can be very inefficient whenthere are many ways to parse a phrase. This work eliminates the multiple parses generated when there is an ambiguous phrase (likea compound noun of five words).<p><li><b>David Walker</b><br><i>Statistical Methods for Part-of-Speech Tagging</i><br><p><li><b>Wee-Liang Heng</b><br><i>Probabilistic Part of Speech Tagging</i><br>This project explores various statistical models                (e.g., smoothed bigram language model) for part-of-speech                tagging, and implements the associated algorithms.  The                models will be evaluated on their accuracy on either the                PennTree Bank or Brown corpus.<p><li><b>Daniel Brown</b><br><i>Text Compression Using NLP</i><br>Most compression schemes take advantage of the fact that certain symbols in the input file are much more likely (frequent) than others.  This project will attempt to take advantage of the fact that certain sequences of words are much more likely than others.  In particular, I will assume that grammatical sentences are much more likely than ungrammatical sentences.  I will encode sentences in such a way that grammatical sentences take up less space.<p></ol><hr><h2>May 1<sup>st</sup></h2><ol><li><b>Heji Kim</b><br><i>Information Extraction from Poetic Forms</i><br>The purpose of this project will be to automatically gather useful information from poems via syntactic/semantic parsing; this informationwill be the search keys to index a corpus of poetry in a database.<p><li><b>Vera Kettnaker</b><br><i>Deriving the Meaning of Novel Words</i><br>The idea of this project is to guess the meaning ofnovel words (first names, abbreviations of new terrorist organizations ect.)on the basis of expectations we gain from the surrounding context.<p><li><b>Grzegorz Czajkowski</b><br><i></i><br><p><li><b>Pavel Naumov</b><br><i>Presentation of Natural Language Sentence in Nuprl Term Editor</i><br>Adopt Nuprl term editor for natural language representation.   Write several ML programs that will extract information   from natural sentences presented in term editor. (say, answer   on simplest questions base on given group of sentences).<p><li><b>Joel Rosenzweig</b><br><i>A Weather Text Processing and Understanding System</i><br>I am writing a grammar suitable for parsing weather text thatI can grab off of the Internet/Weather Channel Web site.  This system willlook for "thematic" roles associated with the text to provide a summary ofthe forecast.  Time permitting, I will make a program that will interpret thissummary data, and generate a weather map that depicts the forecast.<p><li><b>Christine R. Paradis</b><br><i>Translating an English Sentence to an SQL Statement</i><br>I will be translating an English sentence to an SQL query.  My initial approach to this problem is to use the thematic role information for a given sentence and map this information to the corresponding SQL constructs.  For evaluation of the system, I will generate SQL statements for a set of test sentences and compare the results with my desired/correct SQL statements.<p></ol></body></html>

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