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IXIR: A Statistical Information Distillation System
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In: http://www.icsi.berkeley.edu/~levit/papers/CSL09_IXIR.pdf (2009)
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A ranking approach to Persian pronoun resolution
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In: http://www.cicling.org/2009/RCS-41/169-180.pdf (2009)
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Automatic expansion of domainspecific lexicons by term categorization
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In: http://tcc.itc.it/people/lavelli/papers/TSLP06.pdf (2004)
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Experiments with a Hindi-toEnglish transfer-based MT system under a miserly data scenario
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In: http://www.mt-archive.info/TALIP-2003-Lavie.pdf (2003)
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On the Portability and Tuning of Supervised Word Sense Disambiguation Systems
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In: http://www.lsi.upc.es/~lluism/drafts/WSDport.ps.gz (2000)
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Using Syntactic Dependencies and WordNet Classes for Noun Event Recognition
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In: http://ceur-ws.org/Vol-902/paper_5.pdf
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Automated Translation between Lexicon and Corpora
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In: http://www.humanamente.eu/PDF/Issue_23_Papers_Gola et al.pdf
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BUILDING AN EFFICIENT, SCALABLE, AND TRAINABLE PROBABILITY-AND-RULE- BASED PART-OF-SPEECH TAGGER OF HIGH ACCURACY by
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In: http://www.ai.uga.edu/IAI/Theses/han_jiayun.pdf
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Extractive Summarisation of Legal Texts
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In: http://www.ltg.ed.ac.uk/np/publications/ltg/papers/Hachey2006Extractive.pdf
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EDUCATING LIA: THE DEVELOPMENT OF A LINGUISTICALLY ACCURATE MEMORY-BASED LEMMATISER FOR AFRIKAANS
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In: http://dl.ifip.org/db/conf/ifip12/iip2006/Groenewald06.pdf
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Tutor Dialogue Planning with Contextual Information and Discourse Structure
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In: http://www.cs.cmu.edu/afs/cs/user/rwfisher/www/Curriculum_Vitae_files/fisher_simmons_its14.pdf
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Abstract:
Abstract. In this paper, we present two techniques to improve the ef-fectiveness of a conversational tutoring system when interacting with groups of users. First, we propose the usage of linguistic features derived from discourse parsing to better understand the structure of the ongo-ing dialogue between the students and the tutoring system. Discourse parsing gives us the relational structure of a dialogue, and can be used to improve the tutoring system’s understanding of conversation struc-ture. Second, we discuss dialogue planning using contextual information stored in a Contextual Knowledge Base (CKB). A conversational agent with access to a information about linguistic and environmental context will be able to respond to changing conditions in ways that a simple question answering agent is not capable of. We present previous empiri-cal results for these two tasks and discuss how they can be incorporated into an Intelligent Tutoring System.
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Keyword:
Discourse Parsing; Intelligent Tutoring Systems; Machine Learning; Natural Language Processing; Spectral Learning
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.696.7840 http://www.cs.cmu.edu/afs/cs/user/rwfisher/www/Curriculum_Vitae_files/fisher_simmons_its14.pdf
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ONTOLOGY SWITCHING FOR THE SOCIAL SCIENCES. METHODS FOR THE UNDERLYING CORPUS ANALYSIS
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In: http://www.stroetgen.de/Dokumente/rc33-2004.pdf
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THE EFFECT OF PARALLEL CORPUS QUALITY VS SIZE IN ENGLISH-TO- TURKISH SMT
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In: http://airccj.org/CSCP/vol4/csit42503.pdf
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A Machine Learning based Textual Entailment Recognition System of JAIST Team for NTCIR9 RITE
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In: http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings9/NTCIR/02-NTCIR9-RITE-PhamM.pdf
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Experience
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In: http://www.desilinguist.org/pdf/madnani-cv.pdf
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CALICO Journal, 26(3)
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In: http://www.research.att.com/people/Stent_Amanda_J/library/publications/napolitanostent_09.pdf
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Taxonomy and Evaluation of Markers for Computational
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In: http://world-comp.org/p2011/ICA3763.pdf
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Gradient for Structured Prediction
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In: http://www.cs.sfu.ca/%7Eanoop/students/porus_patell/poruspatell-mscProject.pdf
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Social Network- An autonomous system designed for radio recommendation.
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In: http://www.cri.ensmp.fr/classement/doc/A-410.pdf
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A Maximum Entropy (ME) Based Translation Model for Chinese Characters Conversion
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In: http://www.cicling.org/2009/RCS-41/267-276.pdf
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