Concordance

Query which 108 (5,035.2 per million)

selection function </term> is presented ,	which	yields superior <term> feature vectors </term>	#5368 Finally, a novel feature weighting and selection function is presented, which yields superior feature vectors and better word similarity performance.
this paper is the first step in a project	which	aims to cluster and summarise <term> electronic	#5392 The work presented in this paper is the first step in a project which aims to cluster and summarise electronic discussions in the context of help-desk applications.
WSD ) system </term> for <term> Dutch </term>	which	combines <term> statistical classification	#5997 In this paper, we present a corpus-based supervised word sense disambiguation (WSD) system for Dutchwhich combines statistical classification (maximum entropy) with linguistic information.
comparison with previous <term> models </term> ,	which	either use arbitrary <term> windows </term>	#6356 In comparison with previous models, which either use arbitrary windows to compute similarity between words or use lexical affinity to create sequential models, in this paper we focus on models intended to capture the co-occurrence patterns of any pair of words or phrases at any distance in the corpus.
</term> , a <term> probabilistic model </term>	which	has performed well on <term> information	#6832 The information extraction system we evaluate is based on a linear-chain conditional random field (CRF), a probabilistic modelwhich has performed well on information extraction tasks because of its ability to capture arbitrary, overlapping features of the input in a Markov model.
takes advantage of the different way in	which	<term> word senses </term> are lexicalised	#6967 Our method takes advantage of the different way in which word senses are lexicalised in English and Chinese, and also exploits the large amount of Chinese text available in corpora and on the Web.
an impediment to progress in the field ,	which	we address with this work . Experiments	#7588 The lack of automatic methods for scoring system output is an impediment to progress in the field, which we address with this work.
instance , <term> statistical MT systems </term>	which	usually segment their <term> outputs </term>	#7780 The use of BLEU at the character level eliminates the word segmentation problem: it makes it possible to directly compare commercial systems outputting unsegmented texts with, for instance, statistical MT systemswhich usually segment their outputs.
classification method </term> based on <term> PER </term>	which	leverages <term> part of speech information	#8377 We also introduce a novel classification method based on PERwhich leverages part of speech information of the words contributing to the word matches and non-matches in the sentence.
</term> . This article considers approaches	which	rerank the output of an existing <term> probabilistic	#8653 This article considers approaches which rerank the output of an existing probabilistic parser.
</term> or a <term> generative model </term>	which	takes these <term> features </term> into account	#8752 The strength of our approach is that it allows a tree to be represented as an arbitrary set of features, without concerns about how these features interact or overlap and without the need to define a derivation or a generative modelwhich takes these features into account.
</term> for the <term> boosting approach </term>	which	takes advantage of the <term> sparsity of	#8872 The article also introduces a new algorithm for the boosting approachwhich takes advantage of the sparsity of the feature space in the parsing data.
applicable to many other <term> NLP problems </term>	which	are naturally framed as <term> ranking tasks	#8961 Although the experiments in this article are on natural language parsing (NLP), the approach should be applicable to many other NLP problemswhich are naturally framed as ranking tasks, for example, speech recognition, machine translation, or natural language generation.
benefit to <term> language pairs </term> for	which	only scarce <term> resources </term> are available	#9114 Thus, our method can be applied with great benefit to language pairs for which only scarce resources are available.
phrase-based statistical machine translation </term>	which	allows for the <term> retrieval </term> of	#9135 In this paper we describe a novel data structure for phrase-based statistical machine translationwhich allows for the retrieval of arbitrarily long phrases while simultaneously using less memory than is required by current decoder implementations.
the <term> machine translation task </term> ,	which	can also be viewed as a <term> stochastic	#9487 Second, we describe the graphical model for the machine translation task, which can also be viewed as a stochastic tree-to-tree transducer.
<term> log-linear block bigram model </term>	which	uses <term> real-valued features </term> (	#9598 We use a maximum likelihood criterion to train a log-linear block bigram modelwhich uses real-valued features (e.g. a language model score) as well as binary features based on the block identities themselves, e.g. block bigram features.
statistical machine translation system </term>	which	performs <term> tree-to-tree translation </term>	#9786 We present a Czech-English statistical machine translation systemwhich performs tree-to-tree translation of dependency structures.
Statistical Machine Translation ( SMT ) </term> but	which	have not been addressed satisfactorily	#9944 In this paper we study a set of problems that are of considerable importance to Statistical Machine Translation (SMT) but which have not been addressed satisfactorily by the SMT research community.
present a new <term> evaluation measure </term>	which	explicitly models <term> block reordering	#10365 In this paper, we will present a new evaluation measurewhich explicitly models block reordering as an edit operation.


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