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logic program </term> is proposed . It is	also	a drastic generalization of <term> chart	#20893 It is also a drastic generalization of chart Parsing, partial instantiation of clauses in a program roughly corresponding to arcs in a chart.
algorithm </term> . In addition , it could	also	be used to help evaluate <term> disambiguation	#19315 In addition, it could also be used to help evaluate disambiguation algorithms that did not make use of the discourse constraint.
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.
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.
</term> in <term> compound nouns </term> , but	also	can find the correct candidates for the	#20434 This method can not only detect Japanese homophone errors in compound nouns, but also can find the correct candidates for the detected errors automatically.
<term> sentence </term> again . This method is	also	capable of handling <term> unknown words </term>	#18228 This method is also capable of handling unknown words, which is important in practical systems.
and the <term> typing location </term> can be	also	changed in lateral or longitudinal directions	#12284 Its selection of fonts, specification of character size are dynamically changeable, and the typing location can be also changed in lateral or longitudinal directions.
interface </term> for browsing and editing was	also	designed and implemented . The principle	#17330 A customized interface for browsing and editing was also designed and implemented.
approximations </term> for these computations . We	also	discuss some practical ways of dealing	#10077 We also discuss some practical ways of dealing with complexity.
aspects of <term> language learning </term> are	also	discussed . Current <term> natural language	#12524 Implications towards automating certain aspects of language learning are also discussed.
vital to <term> machine translation </term> are	also	discussed together with various interesting	#13314 Some examples of the difference between Japanese sentence structure and English sentence structure, which is vital to machine translation are also discussed together with various interesting ambiguities.
different <term> inference types </term> . The paper	also	discusses how <term> memory </term> is structured	#12020 The paper also discusses how memory is structured in multiple ways to support the different inference types, and how the information found in memory determines which inference types are triggered.
given biased <term> gold standard </term> it	also	enables <term> automatic parameter optimization	#10225 Offering advantages like reproducability and independency of a given biased gold standard it also enables automatic parameter optimization of the WSI algorithm.
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.
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> , and <term> word matchings </term> , are	also	factored in by modifying the <term> transition	#21351 Other contextual clues, such as editing terms, word fragments, and word matchings, are also factored in by modifying the transition probabilities.
indicators for the top-level prediction task . We	also	find that the <term> transcription errors	#10609 We also find that the transcription errors inevitable in ASR output have a negative impact on models that combine lexical-cohesion and conversational features, but do not change the general preference of approach for the two tasks.
96 % and a <term> recall </term> of 98 % . It	also	gets a <term> precision </term> of 70 % and	#11262 It also gets a precision of 70% and a recall of 49% in the task of placing commas.
can make a fair copy of not only texts but	also	graphs and tables indispensable to our	#12256 In this paper, we report a system FROFF which can make a fair copy of not only texts but also graphs and tables indispensable to our papers.
<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.


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