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lr,1-3-P03-1050,bq	training resources </term> . No <term> parallel	text	</term> is needed after the <term> training	#4478 No parallel text is needed after the training phase.
other,37-3-N03-1018,bq	translation lexicons </term> from <term> printed	text	</term> . We present an application of <term>	#2782 We present an implementation of the model based on finite-state models, demonstrate the model's ability to significantly reduce character and word error rate, and provide evaluation results involving automatic extraction of translation lexicons from printed text.
other,12-4-P06-1013,bq	are derived automatically from <term> raw	text	</term> . Experiments using the <term> SemCor	#11022 Our combination methods rely on predominant senses which are derived automatically from raw text.
	aggregation system </term> using each author 's	text	as a coherent <term> corpus </term> . Our approach	#6133 This paper proposes a new methodology to improve the accuracy of a term aggregation system using each author's text as a coherent corpus.
other,20-2-P01-1008,bq	translations </term> of the same <term> source	text	</term> . Our approach yields <term> phrasal	#1798 We present an unsupervised learning algorithm for identification of paraphrases from a corpus of multiple English translations of the same source text.
tech,36-1-H01-1040,bq	text collections </term> via a standard <term>	text	browser </term> . We describe how this information	#310 In this paper we show how two standard outputs from information extraction (IE) systems - named entity annotations and scenario templates - can be used to enhance access to text collections via a standardtext browser.
other,28-1-C86-1132,bq	sublanguages </term> with <term> stereotyped	text	structure </term> . <term> RAREAS </term> draws	#13943 This paper describes a system (RAREAS) which synthesizes marine weather forecasts directly from formatted weather data. Such synthesis appears feasible in certain natural sublanguages with stereotyped text structure.
other,14-4-C92-4207,bq	spatial constraints </term> from the <term>	text	</term> , and represent them as the <term>	#18468 To reconstruct the model, the authors extract the qualitative spatial constraints from thetext, and represent them as the numerical constraints on the spatial attributes of the entities.
other,29-3-P84-1078,bq	antecedence </term> of each element in the <term>	text	</term> to select the proper <term> substitutions	#13816 The system identities a strength of antecedence recovery for each of the lexical substitutions, and matches them against the strength of potential antecedence of each element in thetext to select the proper substitutions for these elements.
other,17-1-A94-1026,bq	conversion </term> needed to input the <term>	text	</term> . It is critical , therefore , for	#20383 Japanese texts frequently suffer from the homophone errors caused by the KANA-KANJI conversion needed to input thetext.
other,37-1-A92-1027,bq	</term> are unknown and much of the <term>	text	</term> is irrelevant to the task . The <term>	#17580 We present an efficient algorithm for chart-based phrase structure parsing of natural language that is tailored to the problem of extracting specific information from unrestricted texts where many of the words are unknown and much of thetext is irrelevant to the task.
other,31-1-H01-1040,bq	- can be used to enhance access to <term>	text	collections </term> via a standard <term> text	#305 In this paper we show how two standard outputs from information extraction (IE) systems - named entity annotations and scenario templates - can be used to enhance access totext collections via a standard text browser.
other,31-1-N03-1018,bq	progressing from generation of <term> true	text	</term> through its transformation into the	#2699 In this paper, we introduce a generative probabilistic optical character recognition (OCR) model that describes an end-to-end process in the noisy channel framework, progressing from generation of true text through its transformation into the noisy output of an OCR system.
lr,0-4-P03-1050,bq	phase </term> . <term> Monolingual , unannotated	text	</term> can be used to further improve the	#4489 Monolingual, unannotated text can be used to further improve the stemmer by allowing it to adapt to a desired domain or genre.
lr,11-4-P04-2010,bq	<term> pronouns </term> in <term> unannotated	text	</term> by using a fully automatic sequence	#7081 Furthermore, we present a standalone system that resolves pronouns in unannotated text by using a fully automatic sequence of preprocessing modules that mimics the manual annotation process.
other,16-7-P03-1050,bq	average precision </term> over <term> unstemmed	text	</term> , and 96 % of the performance of	#4586 Task-based evaluation using Arabic information retrieval indicates an improvement of 22-38% in average precision over unstemmed text, and 96% of the performance of the proprietary stemmer above.
other,13-2-N03-2003,bq	data </term> can be supplemented with <term>	text	</term> from the <term> web </term> filtered	#3041 In this paper, we show how training data can be supplemented withtext from the web filtered to match the style and/or topic of the target recognition task, but also that it is possible to get bigger performance gains from the data by using class-dependent interpolation of N-grams.
tech,25-1-H94-1084,bq	<term> image understanding </term> with <term>	text	understanding </term> . Our <term> document	#21385 Because of the complexity of documents and the variety of applications which must be supported, document understanding requires the integration of image understanding withtext understanding.


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