Concordance

Query C04-1036 12 >
Random sample 12 (559.5 per million)

other,9-1-C04-1036,bq	We suggest a new goal and evaluation criterion for <term> word similarity measures </term> .	#5286 We suggest a new goal and evaluation criterion forword similarity measures.
measure(ment),4-2-C04-1036,bq	The new criterion - <term> meaning-entailing substitutability </term> - fits the needs of <term> semantic-oriented NLP applications </term> and can be evaluated directly ( independent of an <term> application </term> ) at a good level of <term> human agreement </term> .	#5294 The new criterion -meaning-entailing substitutability - fits the needs of semantic-oriented NLP applications and can be evaluated directly (independent of an application) at a good level of human agreement.
tech,11-2-C04-1036,bq	The new criterion - <term> meaning-entailing substitutability </term> - fits the needs of <term> semantic-oriented NLP applications </term> and can be evaluated directly ( independent of an <term> application </term> ) at a good level of <term> human agreement </term> .	#5301 The new criterion - meaning-entailing substitutability - fits the needs ofsemantic-oriented NLP applications and can be evaluated directly (independent of an application) at a good level of human agreement.
other,23-2-C04-1036,bq	The new criterion - <term> meaning-entailing substitutability </term> - fits the needs of <term> semantic-oriented NLP applications </term> and can be evaluated directly ( independent of an <term> application </term> ) at a good level of <term> human agreement </term> .	#5313 The new criterion - meaning-entailing substitutability - fits the needs of semantic-oriented NLP applications and can be evaluated directly (independent of anapplication) at a good level of human agreement.
other,30-2-C04-1036,bq	The new criterion - <term> meaning-entailing substitutability </term> - fits the needs of <term> semantic-oriented NLP applications </term> and can be evaluated directly ( independent of an <term> application </term> ) at a good level of <term> human agreement </term> .	#5320 The new criterion - meaning-entailing substitutability - fits the needs of semantic-oriented NLP applications and can be evaluated directly (independent of an application) at a good level ofhuman agreement.
other,11-3-C04-1036,bq	Motivated by this semantic criterion we analyze the empirical quality of <term> distributional word feature vectors </term> and its impact on <term> word similarity </term> results , proposing an objective <term> measure </term> for evaluating <term> feature vector </term> quality .	#5334 Motivated by this semantic criterion we analyze the empirical quality ofdistributional word feature vectors and its impact on word similarity results, proposing an objective measure for evaluating feature vector quality.
other,19-3-C04-1036,bq	Motivated by this semantic criterion we analyze the empirical quality of <term> distributional word feature vectors </term> and its impact on <term> word similarity </term> results , proposing an objective <term> measure </term> for evaluating <term> feature vector </term> quality .	#5342 Motivated by this semantic criterion we analyze the empirical quality of distributional word feature vectors and its impact onword similarity results, proposing an objective measure for evaluating feature vector quality.
measure(ment),26-3-C04-1036,bq	Motivated by this semantic criterion we analyze the empirical quality of <term> distributional word feature vectors </term> and its impact on <term> word similarity </term> results , proposing an objective <term> measure </term> for evaluating <term> feature vector </term> quality .	#5349 Motivated by this semantic criterion we analyze the empirical quality of distributional word feature vectors and its impact on word similarity results, proposing an objectivemeasure for evaluating feature vector quality.
other,29-3-C04-1036,bq	Motivated by this semantic criterion we analyze the empirical quality of <term> distributional word feature vectors </term> and its impact on <term> word similarity </term> results , proposing an objective <term> measure </term> for evaluating <term> feature vector </term> quality .	#5352 Motivated by this semantic criterion we analyze the empirical quality of distributional word feature vectors and its impact on word similarity results, proposing an objective measure for evaluatingfeature vector quality.
tech,4-4-C04-1036,bq	Finally , a novel <term> feature weighting and selection function </term> is presented , which yields superior <term> feature vectors </term> and better <term> word similarity </term> performance .	#5360 Finally, a novelfeature weighting and selection function is presented, which yields superior feature vectors and better word similarity performance.
other,15-4-C04-1036,bq	Finally , a novel <term> feature weighting and selection function </term> is presented , which yields superior <term> feature vectors </term> and better <term> word similarity </term> performance .	#5371 Finally, a novel feature weighting and selection function is presented, which yields superiorfeature vectors and better word similarity performance.
other,19-4-C04-1036,bq	Finally , a novel <term> feature weighting and selection function </term> is presented , which yields superior <term> feature vectors </term> and better <term> word similarity </term> performance .	#5375 Finally, a novel feature weighting and selection function is presented, which yields superior feature vectors and betterword similarity performance.


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