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Zernik87 ] . Second , we show in this paper	how	a <term> lexical hierarchy </term> is used	#15875 Second, we show in this paper how a lexical hierarchy is used in predicting new linguistic concepts.
that <term> users </term> need by analyzing	how	a <term> user </term> interacts with a system	#11680 FERRET utilizes a novel approach to Q/A known as predictive questioning which attempts to identify the questions (and answers) that users need by analyzing how a user interacts with a system while gathering information related to a particular scenario.
documentation . The question is , however ,	how	an interesting information piece would	#42 The question is, however, how an interesting information piece would be found in a large database.
restrictive statements </term> . The paper shows	how	conventional algorithms for the analysis	#15307 The paper shows how conventional algorithms for the analysis of context free languages can be adapted to the CCR formalism.
</term> , the <term> theory </term> specifies	how	different information in <term> memory </term>	#11951 Unlike logic, the theory specifies how different information in memory affects the certainty of the conclusions drawn.
this <term> complexity </term> , we describe	how	<term> disjunctive </term> values can be specified	#14841 To deal with this complexity, we describe how disjunctive values can be specified in a way which delays expansion to disjunctive normal form.
</term> in <term> English </term> . We demonstrate	how	errors in the <term> machine translations	#7222 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.
translation probabilities </term> , and show	how	it can be refined to take <term> contextual	#9739 We define a paraphrase probability that allows paraphrases extracted from a bilingual parallel corpus to be ranked using translation probabilities, and show how it can be refined to take contextual information into account.
characterization of what a <term> user model </term> is and	how	it can be used . The types of information	#16061 It begins with a characterization of what a user model is and how it can be used.
</term> . The demonstration will focus on	how	<term> JAVELIN </term> processes <term> questions	#3667 The demonstration will focus on how JAVELIN processes questions and retrieves the most likely answer candidates from the given text corpus.
context . We identified two tasks : First ,	how	<term> linguistic concepts </term> are acquired	#15843 First, how linguistic concepts are acquired from training examples and organized in a hierarchy; this task was discussed in previous papers [Zernik87].
inference types </term> . The paper also discusses	how	<term> memory </term> is structured in multiple	#12022 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.
translation systems </term> , and demonstrate	how	our application can be used by <term> developers	#7662 We incorporate this analysis into a diagnostic tool intended for developers of machine translation systems, and demonstrate how our application can be used by developers to explore patterns in machine translation output.
statistical machine translation </term> , we show	how	<term> paraphrases </term> in one <term> language	#9698 Using alignment techniques from phrase-based statistical machine translation, we show how paraphrases in one language can be identified using a phrase in another language as a pivot.
based on processing . Finally , it shows	how	processing accounts can be described formally	#21196 Finally, it shows how processing accounts can be described formally and declaratively in terms of Dynamic Grammars.
context of <term> dialog systems </term> . We show	how	research in <term> generation </term> can be	#997 We show how research in generation can be adapted to dialog systems, and how the high cost of hand-crafting knowledge-based generation systems can be overcome by employing machine learning techniques.
array-based data structure </term> . We show	how	<term> sampling </term> can be used to reduce	#9180 We show how sampling can be used to reduce the retrieval time by orders of magnitude with no loss in translation quality.
set representation </term> . We investigate	how	sets of individually high-precision <term>	#20071 We investigate how sets of individually high-precision rules can result in a low precision when used together, and develop some theory about these probably-correct rules.
time </term> . Furthermore , we will show	how	some <term> evaluation measures </term> can	#10390 Furthermore, we will show how some evaluation measures can be improved by the introduction of word-dependent substitution costs.
broad range of <term> texts </term> to show	how	the distribution of <term> demonstrative	#15202 We examine a broad range of texts to show how the distribution of demonstrative forms and functions is genre dependent.


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