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.
<term> machine translation systems </term> .	This	, the first experiment in a series of experiments	#609 We believe that these evaluation techniques will provide information about both the human language learning process, the translation process and the development of machine translation systems. This, the first experiment in a series of experiments, looks at the intelligibility of MT output.
</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.
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.
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.
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.
enable high quality <term> IE </term> results .	This	paper proposes the <term> Hierarchical Directed	#3789 The experimental results prove our claim that accurate predicate-argument structures enable high quality IE results. This paper proposes the Hierarchical Directed Acyclic Graph (HDAG) Kernel for structured natural language data.
Experimental results validate our hypothesis .	This	paper concerns the <term> discourse understanding	#4126 Experimental results validate our hypothesis. This paper concerns the discourse understanding process in spoken dialogue systems.
</term> in <term> spoken dialogue systems </term> .	This	process enables the <term> system </term> to	#4138 This paper concerns the discourse understanding process in spoken dialogue systems. This process enables the system to understand user utterances based on the context of a dialogue.
understanding accuracy </term> can be improved .	This	paper proposes a method for resolving this	#4216 By holding multiple candidates for understanding results and resolving the ambiguity as the dialogue progresses, the discourse understanding accuracy can be improved. This paper proposes a method for resolving this ambiguity based on statistical information obtained from dialogue corpora.
duration </term> for <term> skilled users </term> .	This	paper presents an <term> unsupervised learning	#4430 Experimental evaluation shows that the cooperative responses adaptive to individual users serve as good guidance for novice users without increasing the dialogue duration for skilled users. This paper presents an unsupervised learning approach to building a non-English (Arabic) stemmer.
investigate the reason for that difference .	This	paper presents a <term> machine learning </term>	#5149 We also investigate the reason for that difference. This paper presents a machine learning approach to bare sluice disambiguation in dialogue.
in a set of coherent <term> corpora </term> .	This	paper proposes a new methodology to improve	#6114 We present a text mining method for finding synonymous expressions based on the distributional hypothesis in a set of coherent corpora. This paper proposes a new methodology to improve the accuracy of a term aggregation system using each author's text as a coherent corpus.
<term> statistical machine translation </term> .	This	statistical approach aims to minimize <term>	#6556 We present Minimum Bayes-Risk (MBR) decoding for statistical machine translation. This statistical approach aims to minimize expected loss of translation errors under loss functions that measure translation performance.
<term> coherence </term> in <term> essays </term> .	This	system identifies <term> features </term> of	#6690 We describe a new system that enhances Criterion's capability, by evaluating multiple aspects of coherence in essays. This system identifies features of sentences based on semantic similarity measures and discourse structure.
datasets </term> , with promising results .	This	paper presents a novel <term> ensemble learning	#7021 We evaluated the topic signatures on a WSD task, where we trained a second-order vector co-occurrence algorithm on standard WSD datasets, with promising results. This paper presents a novel ensemble learning approach to resolving German pronouns.
</term> , focusing on <term> noun phrases </term> .	This	paper presents a <term> maximum entropy word	#7249 We demonstrate how errors in the machine translations of the input Arabic documents can be corrected by identifying and generating from such redundancy, focusing on noun phrases. This paper presents a maximum entropy word alignment algorithm for Arabic-English based on supervised training data.
<term> human annotation performance </term> .	This	paper presents a <term> phrase-based statistical	#7337 Performance of the algorithm is contrasted with human annotation performance. This paper presents a phrase-based statistical machine translation method, based on non-contiguous phrases, i.e. phrases with gaps.
generalize from the <term> training data </term> .	This	paper investigates some <term> computational	#7434 Experimental results are presented, that demonstrate how the proposed method allows to better generalize from the training data. This paper investigates some computational problems associated with probabilistic translation models that have recently been adopted in the literature on machine translation.
the <term> word segmentation problem </term> .	This	study establishes the equivalence between	#7724 Yet, they are scarcely used for the assessment of language pairs like English-Chinese or English-Japanese, because of the word segmentation problem. This study establishes the equivalence between the standard use of BLEU in word n-grams and its application at the character level.


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