Concordance

Query also 46 (2,144.6 per million)

carries important information yet it is	also	time consuming to document . Given the	#11 Oral communication is ubiquitous and carries important information yet it is also time consuming to document.
<term> industry watch </term> function . We	also	report results of a preliminary , <term>	#345 We also report results of a preliminary, qualitative user evaluation of the system, which while broadly positive indicates further work needs to be done on the interface to make users aware of the increased potential of IE-enhanced text browsers.
database </term> . <term> Requestors </term> can	also	instruct the <term> system </term> to notify	#866 Requestors can also instruct the system to notify them when the status of a request changes or when a request is complete.
language identification </term> . The paper	also	proposes <term> rule-reduction algorithm </term>	#1264 The paper also proposes rule-reduction algorithm applying mutual information to reduce the error-correction rules.
retrieval accuracy </term> , but much faster . We	also	provide evidence that our findings are	#1588 We also provide evidence that our findings are scalable.
to perform an exhaustive comparison , we	also	evaluate a <term> hand-crafted template-based	#2080 In order to perform an exhaustive comparison, we also evaluate a hand-crafted template-based generation component, two rule-based sentence planners, and two baseline sentence planners.
target <term> recognition task </term> , but	also	that it is possible to get bigger performance	#3059 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.
predicate-argument structures </term> . We	also	introduce a new way of automatically identifying	#3730 We also introduce a new way of automatically identifying predicate argument structures, which is central to our IE paradigm.
<term> sense coverage </term> . Our analysis	also	highlights the importance of the issue	#4917 Our analysis also highlights the importance of the issue of domain dependence in evaluating WSD programs.
</term> than that of <term> LTAG </term> . We	also	investigate the reason for that difference	#5141 We also investigate the reason for that difference.
source-channel transliteration model </term> ,	also	called <term> n-gram transliteration model	#5783 Under this framework, a joint source-channel transliteration model, also called n-gram transliteration model (ngram TM), is further proposed to model the transliteration process.
extensive system development effort but	also	improves the <term> transliteration accuracy	#5835 Our study reveals that the proposed method not only reduces an extensive system development effort but also improves the transliteration accuracy significantly.
English </term> and <term> Chinese </term> , and	also	exploits the large amount of <term> Chinese	#6978 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.
<term> statistical translation model </term> is	also	presented that deals such <term> phrases </term>	#7375 A statistical translation model is also presented that deals such phrases, as well as a training method based on the maximization of translation accuracy, as measured with the NIST evaluation metric.
of <term> CMU 's SMT system </term> . It has	also	successfully been coupled with <term> rule-based	#8170 It has also successfully been coupled with rule-based and example based machine translation modules to build a multi engine machine translation system.
research </term> . This piece of work has	also	laid a foundation for exploring and harvesting	#8298 This piece of work has also laid a foundation for exploring and harvesting English-Chinese bitexts in a larger volume from the Web.
equivalence </term> and <term> entailment </term> . We	also	introduce a novel <term> classification method	#8368 We also introduce a novel classification method based on PER which leverages part of speech information of the words contributing to the word matches and non-matches in the sentence.
model ’s score </term> of 88.2 % . The article	also	introduces a new <term> algorithm </term> for	#8863 The article also introduces a new algorithm for the boosting approach which takes advantage of the sparsity of the feature space in the parsing data.
statistical machine translation system </term> . We	also	show that a good-quality <term> MT system	#9069 We also show that a good-quality MT system can be built from scratch by starting with a very small parallel corpus (100,000 words) and exploiting a large non-parallel corpus.
machine translation task </term> , which can	also	be viewed as a <term> stochastic tree-to-tree	#9489 Second, we describe the graphical model for the machine translation task, which can also be viewed as a stochastic tree-to-tree transducer.


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