Concordance

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planning , informing , story-telling , etc .	This	paper addresses the problem of the <term>	#107 An alternative index could be the activity such as discussing, planning, informing, story-telling, etc. This paper addresses the problem of the automatic detection of those activities in meeting situation and everyday rejoinders.
Communicator </term> participants are using . In	this	presentation , we describe the features	#254 In this presentation, we describe the features of and requirements for a genuinely useful software infrastructure for this purpose.
infrastructure </term> for this purpose . In	this	paper we show how two standard outputs	#275 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 standard text browser.
original document </term> . The purpose of	this	research is to test the efficacy of applying	#547 The purpose of this research is to test the efficacy of applying automated evaluation techniques, originally devised for the evaluation of human language learners, to the output of machine translation (MT) systems.
built and will demonstrate an application of	this	approach called <term> LCS-Marine </term> .	#823 We have built and will demonstrate an application of this approach called LCS-Marine.
<term> machine learning techniques </term> . In	this	paper , we address the problem of combining	#1028 In this paper, we address the problem of combining several language models (LMs).
performance </term> . We describe our use of	this	approach in numerous fielded <term> user	#1228 We describe our use of this approach in numerous fielded user studies conducted with the U.S. military.
</term> conducted with the U.S. military .	This	paper proposes a practical approach employing	#1241 We describe our use of this approach in numerous fielded user studies conducted with the U.S. military. This paper proposes a practical approach employing n-gram models and error-correction rules for Thai key prediction and Thai-English language identification.
into one or more <term> sentences </term> . In	this	paper , we present <term> SPoT </term> , a <term>	#1336 In this paper, we present SPoT, a sentence planner, and a new methodology for automatically training SPoT on the basis of feedback provided by human judges.
top human-ranked sentence plan </term> . In	this	paper , we compare the relative effects	#1462 In this paper, we compare the relative effects of segment order, segmentation and segment contiguity on the retrieval performance of a translation memory system.
parsed in <term> O ( n6 ) time </term> . In	this	paper , we study a <term> parsing technique	#1680 In this paper, we study a parsing technique whose purpose is to improve the practical efficiency of RCL parsers.
well as <term> syntactic paraphrases </term> .	This	paper presents a <term> formal analysis </term>	#1815 Our approach yields phrasal and single word lexical paraphrases as well as syntactic paraphrases. This paper presents a formal analysis for a large class of words called alternative markers, which includes other (than), such (as), and besides.
template-based or rule-based approaches </term> . In	this	paper We experimentally evaluate a <term>	#2051 In this paper We experimentally evaluate a trainable sentence planner for a spoken dialogue system by eliciting subjective human judgments.
relationships among the target variables .	This	paper describes a method for <term> utterance	#2205 We report on different aspects of the predictive performance of our models, including the influence of various training and testing factors on predictive performance, and examine the relationships among the target variables. This paper describes a method for utterance classification that does not require manual transcription of training data.
<term> average precision metric </term> . In	this	paper we present <term> ONTOSCORE </term> ,	#2436 In this paper we present ONTOSCORE, a system for scoring sets of concepts on the basis of an ontology.
performance of our <term> systems </term> . In	this	paper , we introduce a <term> generative	#2668 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.
conversational speech </term> are limited . In	this	paper , we show how <term> training data </term>	#3029 In this paper, we show how training data can be supplemented with text 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.
sentence </term> . We evaluate the utility of	this	<term> constraint </term> in two different <term>	#3264 We evaluate the utility of this constraint in two different algorithms.
successive learners </term> is presented .	This	approach only requires a few <term> common	#3305 A novel bootstrapping approach to Named Entity (NE) tagging using concept-based seeds and successive learners is presented. This approach only requires a few common noun or pronoun seeds that correspond to the concept for the targeted NE, e.g. he/she/man/woman for PERSON NE.
performance for some <term> NE types </term> . In	this	paper , we describe a <term> phrase-based	#3390 In this paper, we describe a phrase-based unigram model for statistical machine translation that uses a much simpler set of model parameters than similar phrase-based models.


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