Concordance

Query C88-2162 22 >
Sort Node 22 (1,025.7 per million)

other,8-4-C88-2162,bq	linguistic representation </term> , the <term>	Dynamic Hierarchical Phrasal Lexicon ( DHPL )	</term> [ Zernik88 ] , to facilitate <term>	#15794 We introduced a new linguistic representation, theDynamic Hierarchical Phrasal Lexicon ( DHPL ) [Zernik88], to facilitate language acquisition.
other,8-2-C88-2162,bq	learning methodology </term> applicable in <term>	general domains	</term> does not readily lend itself in the	#15758 For one thing, learning methodology applicable ingeneral domains does not readily lend itself in the linguistic domain.
other,14-7-C88-2162,bq	examples </term> and organized in a <term>	hierarchy	</term> ; this task was discussed in previous	#15855 First, how linguistic concepts are acquired from training examples and organized in ahierarchy; this task was discussed in previous papers [Zernik87].
other,18-9-C88-2162,bq	<term> lexical unknown </term> , and a <term>	hypothesis	</term> can be produced for covering that	#15905 Thus, a program does not stall even in the presence of a lexical unknown, and ahypothesis can be produced for covering that lexical gap.
tech,21-4-C88-2162,bq	</term> [ Zernik88 ] , to facilitate <term>	language acquisition	</term> . From this , a <term> language learning	#15807 We introduced a new linguistic representation, the Dynamic Hierarchical Phrasal Lexicon (DHPL) [Zernik88], to facilitatelanguage acquisition.
other,4-5-C88-2162,bq	acquisition </term> . From this , a <term>	language learning model	</term> was implemented in the program <term>	#15814 From this, alanguage learning model was implemented in the program RINA, which enhances its own lexical hierarchy by processing examples in context.
tech,7-3-C88-2162,bq	linguistic representation </term> used by <term>	language processing systems	</term> is not geared to <term> learning </term>	#15777 For another, linguistic representation used bylanguage processing systems is not geared to learning.
other,14-3-C88-2162,bq	processing systems </term> is not geared to <term>	learning	</term> . We introduced a new <term> linguistic	#15784 For another, linguistic representation used by language processing systems is not geared tolearning.
other,4-2-C88-2162,bq	acquisition </term> . For one thing , <term>	learning methodology	</term> applicable in <term> general domains	#15754 For one thing,learning methodology applicable in general domains does not readily lend itself in the linguistic domain.
other,25-9-C88-2162,bq	</term> can be produced for covering that <term>	lexical gap	</term> . Although every <term> natural language	#15912 Thus, a program does not stall even in the presence of a lexical unknown, and a hypothesis can be produced for covering thatlexical gap.
other,18-5-C88-2162,bq	RINA </term> , which enhances its own <term>	lexical hierarchy	</term> by processing examples in context	#15828 From this, a language learning model was implemented in the program RINA, which enhances its ownlexical hierarchy by processing examples in context.
other,9-8-C88-2162,bq	Second , we show in this paper how a <term>	lexical hierarchy	</term> is used in predicting new <term> linguistic	#15877 Second, we show in this paper how alexical hierarchy is used in predicting new linguistic concepts.
other,13-9-C88-2162,bq	not stall even in the presence of a <term>	lexical unknown	</term> , and a <term> hypothesis </term> can	#15900 Thus, a program does not stall even in the presence of alexical unknown, and a hypothesis can be produced for covering that lexical gap.
other,3-7-C88-2162,bq	identified two tasks : First , how <term>	linguistic concepts	</term> are acquired from <term> training examples	#15844 First, howlinguistic concepts are acquired from training examples and organized in a hierarchy; this task was discussed in previous papers [Zernik87].
other,16-8-C88-2162,bq	hierarchy </term> is used in predicting new <term>	linguistic concepts	</term> . Thus , a <term> program </term> does	#15884 Second, we show in this paper how a lexical hierarchy is used in predicting newlinguistic concepts.
other,17-2-C88-2162,bq	does not readily lend itself in the <term>	linguistic domain	</term> . For another , <term> linguistic representation	#15767 For one thing, learning methodology applicable in general domains does not readily lend itself in thelinguistic domain.
other,3-3-C88-2162,bq	linguistic domain </term> . For another , <term>	linguistic representation	</term> used by <term> language processing	#15773 For another,linguistic representation used by language processing systems is not geared to learning.
other,4-4-C88-2162,bq	learning </term> . We introduced a new <term>	linguistic representation	</term> , the <term> Dynamic Hierarchical Phrasal	#15790 We introduced a newlinguistic representation, the Dynamic Hierarchical Phrasal Lexicon (DHPL) [Zernik88], to facilitate language acquisition.
tech,9-1-C88-2162,bq	programs so far have not fared well in <term>	modeling language acquisition	</term> . For one thing , <term> learning methodology	#15746 Computer programs so far have not fared well inmodeling language acquisition.
other,3-9-C88-2162,bq	linguistic concepts </term> . Thus , a <term>	program	</term> does not stall even in the presence	#15890 Thus, aprogram does not stall even in the presence of a lexical unknown, and a hypothesis can be produced for covering that lexical gap.


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