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UPenn - DOE - 2005
Penn CDF B Physics OverviewJoseph Kroll Penn DOE Site Visit 8 August 2005Topics Bs & B0 Flavor oscillations ( ms) leadership Kroll, Jones, Oldeman flavor tagging Jones, Usynin, Kroll lifetime resolution Heijboer trigger monitoring & innov
UPenn - DOE - 2005
CDF OverviewJoseph Kroll Penn DOE Site Visit 8 9 August 2005Context of this presentationPast 4 years CDF II has moved from construction & commissioning maintaining & analyzing Penn CDF Group has made major contributions to CDF II & made a major
UPenn - UCC - 1
1-105. Territorial Application of the Act; Parties Power to ChooseApplicable Law and Judicial Forum(a) Unless the law determining the rights and obligations of parties with respect to anyaspect of a transaction governed by this Act has been se
UPenn - N - 03
Statistical Phrase-Based Translation Proceedingsof HLT-NAACL 2003 Main Papers , pp. 48-54 Edmonton, May-June 2003Philipp Koehn, Franz Josef Och, Daniel Marcu Information Sciences Institute Department of Computer Science University of Southern Cal
UPenn - C - 96
H M M - B a s e d Word Alignment in Statistical TranslationStephan Vogel Hermann Ney Christoph Tillmann L e h r s t u h l ffir I n f o r m a t i k V, R W T H A a c h e n D-52056 Aachen, Germany {vogel, n e y , t illmann}@inf ormat ik. rwth-aachen, d
UPenn - P - 03
Chunk-based Statistical TranslationTaro Watanabe, Eiichiro Sumita and Hiroshi G. Okuno {taro.watanabe, eiichiro.sumita}@atr.co.jp ATR Spoken Language Translation Department of Intelligence Science Research Laboratories and Technology 2-2-2 Hikarida
UPenn - C - 00
ABL: Alignment-Based LearningMenno van Zaanen School of C o m p u t e r S t u d i e s University of Leeds LS2 9 J T L(~eds UK menno@scs, l e e d s , a c . ukAbstract This ])al)er introdu(:es a new tyl)e of grammar learning algorithm, iilst)ired l)
UPenn - P - 00
An Information-Theory-Based Feature Type Analysis for the Modelling of Statistical ParsingSUI Zhifang , ZHAO Jun , Dekai WU Hong Kong University of Science & Technology Department of Computer Science Human Language Technology Center Clear Water B
UPenn - P - 03
A spoken dialogue interface for TV operations based on data collected by using WOZ methodJun Yeun-Bae Goto Kim NHK STRL NHK STRL Human Science Human Science Tokyo 157-8510 Tokyo 157-8510 Japan Japangoto.j-fw @nhk.or.jp kimu.y-go @nhk.or.jpMasaru
UPenn - P - 03
Loosely Tree-Based Alignment for Machine TranslationDaniel Gildea University of Pennsylvania dgildea@cis.upenn.eduAbstractWe augment a model of translation based on re-ordering nodes in syntactic trees in order to allow alignments not conforming
UPenn - C - 90
Toward Memory-based TranslationSatoshi S A T O and Ma.koto N A G A O Dept. of Electrical Engineering, K y o t o University Y o s h i d a - h o n m a c h i , Sa.kyo, K.yoto, 606, Ja.pan sa.to@kuee.kyoto-u.ac.jpAbstractAn essential problem of examp
UPenn - J - 93
Machine Translation: A Knowledge-Based Approach Sergei Nirenburg, Jaime Carbonell, Masaru Tomita, and Kenneth Goodman(Carnegie Mellon University) San Mateo, CA: Morgan Kaufmann Publishers, 1992, xiv + 258 pp. Hardbound, ISBN 1-55860-128-7, $39.95T
UPenn - C - 00
Automatic Corpus-Based Thai Word Extraction with the C4.5 Learning AlgorithmVIRACH SORNLERTLAMVANICH, TANAPONG POTIPITI AND THATSANEE CHAROENPORN National Electronics and Computer Technology Centel, National Science and Technology Development Agency
UPenn - C - 90
Reversible Unification Based M a c h m . FranslatlonGertjan van Noord OTS RUU Trans 10 3,512 JK Utrecht Valmoord~hutruu59.BH~netMarch 28, 1990Abstract[n this paper it will be shown how unification g r a m m a r s can be used to build a reversib
UPenn - C - 00
Chart-Based Transfer Rule Application in Machine TranslationAdam MeyersNew York University meyers@cs.nyu.edu M i c h i k o Kosaka Monlnouth University kosaka@monmouth.eduR a l p h GrishInanNew York University grishman@cs.nyu.eduAbstract35"ans
UPenn - P - 99
Corpus-Based Identification of Non-Anaphoric N o u n PhrasesD a v i d L. B e a n and E l l e n R i l o f fD e p a r t m e n t of C o m p u t e r Science University of U t a h Salt Lake City, U t a h 84112 {bean,riloff}@cs.utah.eduAbstract Corefer
UPenn - P - 90
ZERO MORPHEMES IN UNIFICATION-BASED COMBINATORY CATEGORIAL GRAMMAR Chinatsu Aone The University of Texas at Austin & MCC 3500 West Balcones Center Dr. Austin, TX 78759 (aone@mcc.com) ABSTRACT In this paper, we report on our use of zero morphemes in U
UPenn - P - 96
A N e w Statistical Parser Based on B i g r a m Lexical D e p e n d e n c i e sCollins* Dept. of Computer and Information Science University of Pennsylvania P h i l a d e l p h i a , P A , 19104, U . S . A . mcollins@gradient, cis.upenn, eduMichae
UPenn - P - 99
Designing a Task-Based Evaluation M e t h o d o l o g y for a Spoken Machine Translation S y s t e mKavita Thomas L a n g u a g e Technologies I n s t i t u t e Carnegie Mellon University 5000 Forbes Avenue P i t t s b u r g h , PA 15213, USAkavita
UPenn - P - 03
An Ontology-based Semantic Tagger for IE systemNarj` s Boufaden e Department of Computer Science Universit de Montr al e e Quebec, H3C 3J7 Canada boufaden@iro.umontreal.caAbstractIn this paper, we present a method for the semantic tagging of word
UPenn - C - 96
NL Domain Explanations in Knowledge Based MATGalia Angelova, Kalina Bontcheva 1Bulgarian Academy of Sciences, Linguistic Modelling Laboratory A c a d . G, B o n c h e v Str. 2 5 A , 1113 S o f i a , B u l g a r i a , { galja,kalina} @ b g c i c t .
UPenn - P - 03
Deverbal Compound Noun Analysis Based on Lexical Conceptual StructureTeruo Koyama Koichi Takeuchi Kyo Kageura Human and Social Information Research Division National Institute of Informatics 2-1-2 Hitotsubashi, Chiyodaku, Tokyo 101-8430, Japan koich
UPenn - D - 07
Large-Scale Named Entity Disambiguation Based on Wikipedia DataSilviu CucerzanMicrosoft Research One Microsoft Way, Redmond, WA 98052, USA silviu@microsoft.comAbstractThis paper presents a large-scale system for the recognition and semantic disa
UPenn - P - 01
A Syntax-based Statistical Translation ModelKenji Yamada and Kevin Knight Information Sciences Institute University of Southern California 4676 Admiralty Way, Suite 1001 Marina del Rey, CA 90292 kyamada,knight @isi.edu AbstractWe present a syntax-b
UPenn - C - 02
Semantics-based Representation for Multimodal Interpretation in Conversational SystemsJoyce ChaiIBM T. J. Watson Research Center 19 Skyline Drive Hawthorne, NY 10532, USA{jchai@us.ibm.com}Abstract To support context-based multimodal interpretati
UPenn - A - 92
A Simple Rule-Based Part of Speech TaggerEric Brill * D e p a r t m e n t of C o m p u t e r S c i e n c e University of Pennsylvania P h i l a d e l p h i a , P e n n s y l v a n i a 19104U.S.A.brill@unagi.cis.upenn.edu Abstract Automatic part o
UPenn - P - 05
A Hierarchical Phrase-Based Model for Statistical Machine TranslationDavid Chiang Institute for Advanced Computer Studies (UMIACS) University of Maryland, College Park, MD 20742, USA dchiang@umiacs.umd.eduAbstractWe present a statistical phrase-b
UPenn - P - 06
Investigations on Event-Based SummarizationMingli Wu Department of Computing The Hong Kong Polytechnic University Kowloon, Hong Kong csmlwu@comp.polyu.edu.hkAbstractWe investigate independent and relevant event-based extractive mutli-document su
UPenn - N - 06
Thai Grapheme-Based Speech RecognitionPaisarn Charoenpornsawat, Sanjika Hewavitharana, Tanja SchultzInteractive Systems Laboratories, School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 {paisarn, sanjika, tanja}@cs.cmu.eduA
UPenn - P - 01
An Algebra for Semantic Construction in Constraint-based GrammarsAnn Copestake Computer Laboratory University of Cambridge New Museums Site Pembroke St, Cambridge, UKaac@cl.cam.ac.ukAlex Lascarides Division of Informatics University of Edinburgh
UPenn - C - 02
Machine Translation Based on NLG from XML-DBYohei Seki Aoyama Gakuin / Department of Informatics, University The Graduate University for Advanced Studies (Sokendai) Abstract Ken'ichi Harada Department of Computing Science Keio UniversityThe purpos
UPenn - E - 06
Word Sense Induction: Triplet-Based Clustering and Automatic EvaluationStefan Bordag Natural Language Processing Department University of Leipzig Germany sbordag@informatik.uni-leipzig.deAbstractIn this paper a novel solution to automatic and uns
UPenn - P - 89
Unification-BasedSemantic InterpretationRobert C. Moore Artificial Intelligence Center SRI International Menlo Park, CA 94025 AbstractWe show how unification can be used to specify the semantic interpretation of natural-language expressions, inc
UPenn - N - 04
Feature-based Pronunciation Modeling for Speech RecognitionKaren Livescu and James Glass MIT Computer Science and Articial Intelligence Laboratory Cambridge, MA 02139, USA {klivescu, glass}@csail.mit.eduAbstractWe present an approach to pronuncia
UPenn - J - 92
Class-Based n-gram Models of Natural LanguageP e t e r F. B r o w n " P e t e r V. d e S o u z a * R o b e r t L. Mercer* IBM T. J. Watson Research Center V i n c e n t J. D e l l a Pietra* J e n i f e r C. Lai*We address the problem of predicting
UPenn - J - 95
Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part-of-Speech TaggingEric Brill*The Johns Hopkins UniversityRecently, there has been a rebirth of empiricism in the field of natural language processing.
UPenn - E - 06
Adaptive Transformation-based Learning for Improving Dictionary TaggingBurcu Karagol-Ayan, David Doermann, and Amy Weinberg Institute for Advanced Computer Studies (UMIACS) University of Maryland College Park, MD 20742 {burcu,doermann,weinberg}@umia
UPenn - E - 06
Phrase-Based Backoff Models for Machine Translation of Highly Inected LanguagesMei Yang Department of Electrical Engineering University of Washington Seattle, WA, USA yangmei@ee.washington.edu Katrin Kirchhoff Department of Electrical Engineering Un
UPenn - P - 04
Towards a Semantic Classication of Spanish Verbs Based on Subcategorisation InformationEva Esteve Ferrer Department of Informatics University of Sussex Brighton, BN1 9QH, UK E.Esteve-Ferrer@sussex.ac.uk AbstractWe present experiments aiming at an a
UPenn - N - 03
A Phrase-Based Unigram Model for Statistical Machine TranslationChristoph Tillmann and Fei Xia IBM T.J. Watson Research Center Yorktown Heights, NY 10598 {ctill,feixia}@us.ibm.comAbstractIn this paper, we describe a phrase-based unigram model fo
UPenn - CIS - 610
TensorTextures: Multilinear Image-Based RenderingM. Alex O. Vasilescu and Demetri Terzopoulos University of Toronto, Department of Computer Science New York University, Courant Institute of Mathematical SciencesFigure 1: Frames from the Treasure C
UPenn - P - 84
Features and ValuesLauri Karttunen University of Texas at Austin Artificial Intelligence Center SRI International and Center for the Study of Language and Information Stanford UniversityAbstractThe paper discusses the linguistic aspects of a new
UPenn - T - 87
Unification a n d the n e w g r a m m a t i s m Steve Pulman University of Cambridge Computer Laboratory Corn Exchange Street Cambridge C B 2 3QG, UK.Whatare w e talking about?The prototypical unification grammar consists of a context-free skel
UPenn - H - 01
Guidelines for Annotating Temporal InformationInderjeet Mani, George WilsonThe MITRE Corporation, W640 11493 Sunset Hills Road Reston, Virginia 20190-5214, USA +1-703-883-6149Lisa FerroThe MITRE Corporation, K329 202 Burlington Road, Rte. 62 Bed
UPenn - C - 86
The computational complexity of sentence derivation in functional unification grammarGraeme Ritchie Department of Artificial Intelligence University of Edinburgh Edinburgh EHI IHNAbstract Functional unification (FU) grammar is a general linguisti
UPenn - E - 87
DECLARATIVE k VIEVNOOEL FOR DEPENDENCY PARSING INTO BLACKBOARD METHOOOLOGY-Vatkonen, K., J i p p i n e n , H., L e h t o t a , A. and Ytltammi, KIELIKOHE-pr~ject, SITRA Foundation P.O.Box 329, S F - 0 0 1 2 1 H e t s i n k i FinLand t e L . i n
UPenn - A - 97
Layout & Language: Preliminary experiments in assigning logical structure to table cellsMatthew Hurst and Shona Douglas Language Technology Group, Human Communication Research Centre, University of Edinburgh, Edinburgh EH8 9LW UK { M a t t h e w . H
UPenn - C - 88
AN I N T E G R A T E D MODEL F O R T H E TREATMENT OF TIME I N MT- SYSTEMSM. Meya Siemens CDS c/Luis Muntadas,5 CORNELLA, 08940-BARCELONA SpainJ. Vidul EUROTRA-E Ctra. Vallvidriera, 25.27 08017-BARCELONAAbstractOne of the ways to achieve a goo
UPenn - C - 90
Towards a Unification-Based PhonologyRichard Wiese Seminar f'dr Allgem. Spraehwissenschaft Heinrich-Heine-Univer sit,it DUsseldorf D-4000 Di.isseldorf 1 wiesedd0rud81.bitnet 1 Introduction. The Problem Phonological theory has undergone a number cf m
UPenn - C - 86
ASAELEMENTARY CONTRACTS PRAGMATIC BASIS OF LANGUAGEINTERACTIONE.L. Pershina A[ Laboratory, Computer Center Siberian Division of the USSR Ae. Sei. Novosibirsk 630090, USSR ABSTRACT Language interaction (LI) as a part of interpersonal communica
UPenn - E - 85
ON THE REPRESENTATION OF QUERY TERM RELATIONS BY SOFT BOOLEAN oPERATORSGerard Salton D e p a r t m e n t o f Computer S c i e n c e Cornell University Ithaca, NY 14853, USAABSTRACT The l a n g u a g e a n a l y s i s component i n m o s t t e x t
UPenn - C - 86
ConceptualLexicon Using an Object-OrientedLanguageShoiehi Y O K O Y A M A Electrotechnical Laboratory Tsukuba, Ibaraki, JapanKenji H A N A K A T A Universitat Stuttgart Stuttgart, F. R. G e r m a n yAbstractThis paper d e s c r i b e s the
UPenn - E - 91
STRUCTURAL NON-CORRESPONDENCE IN TRANSLATION Henry S. Thompson, Human Communication Research Centre, University of Edinburgh, 2 Buccleuch Place, Edinburgh, EH8 9LW, UIC ht@uk.ac.ed.cogsciLouisa Sadler, Dept. of Language and Linguistics, University
UPenn - C - 82
ADAPTIVE DIALOGUE - THE BASIS FOR PERSONAL COMPUTER SYSTEMVictor Briabrin Computing C e n t e r , Academy o f S c i e n c e s , Hosoow, USSR1. P e r s o n a l Computer S y s t e m s (POS) r e p r e s e n t nowadays a s i g n i f t e a u t t r e n
UPenn - C - 90
Complex Features in Description of Chinese LanguageFeng Zhiwei Imtitute of Applied Linguistics Chinese Academy of Social Sciences 51 Chaoyangmen Nanxiaojie 100010 Beijing, ChinaAbstract In this paper, the similarity of" multi-vahw label fimction" a
UPenn - C - 96
CHINESE STRING SEARCHING USING TtIE K M P ALGORITHMRobert W.P. LukDepartment of Computing, Hong Kong Polytechnic University,Kowloon,Hong Kong E-mail: csrluk@comp.polyu.edu.hkAbstract This paper is about the modification of KMP (Knuth, Morris and
UPenn - CIT - 591
ArraysApr 10, 2009A problem with simple variablesOne variable holds one valueThe value may change over time, but at any given time, a variable holds a single value If you want to keep track of many values, you need many variables All
UPenn - CIT - 591
Numbers and ArraysWidening and narrowing Numeric types are arranged in a continuum: Wider double float long int short byte,char Narrower You can easily assign a narrower type to a wider type: doublewide; intnarrow; wide=narrow; But if you want
UPenn - STAT - 112
Stat 112Review Notes for Chapter 4, Lecture Notes 6-91. Best Simple Linear Regression: Among the variables X 1 , K , X K , the variable which best predicts Y based on a simple linear regression is the variable for which the simple linear regressi
Auburn Montgomery - MATH - 190
Decimal Expansion of FractionsBrent MurphyP QProblem: Under What conditions will the decimal expansion of p/q terminate? Under what conditions will it repeat? p/q can be investigated as p*(1/q).Terminating When placing 1 over q as a fraction t
Auburn Montgomery - MATH - 190
Project 1.2 Decimal Expansions of Rational NumbersJacob Brozenick Anthony Mayle Kenny Milnes And Tim SweetserProblem Descriptions1. Determine which values of q in the expression p/q will cause the termination of the resulting decimal expansion.