| performance </term> further . We suggest a | method | that mimics the behavior of the <term> oracle | #1155 We suggest a method that mimics the behavior of the oracle using a neural network or a decision tree. | |
| tech,8-6-P01-1007,bq | </term><term> evaluation </term> of this <term> | method | </term> on a <term> wide coverage English grammar | #1743 The results of a practical evaluation of thismethod on a wide coverage English grammar are given. |
| target variables . This paper describes a | method | for <term> utterance classification </term> | #2209 This paper describes a method for utterance classification that does not require manual transcription of training data. | |
| <term> HDAGs </term> . We applied the proposed | method | to <term> question classification </term> and | #3843 We applied the proposed method to question classification and sentence alignment tasks to evaluate its performance as a similarity measure and a kernel function. | |
| </term> can be improved . This paper proposes a | method | for resolving this <term> ambiguity </term> | #4220 This paper proposes a method for resolving this ambiguity based on statistical information obtained from dialogue corpora. | |
| occurrences of a <term> morpheme </term> ) . Our | method | is seeded by a small <term> manually segmented | #4639 Our method is seeded by a small manually segmented Arabic corpus and uses it to bootstrap an unsupervised algorithm to build the Arabic word segmenter from a large unsegmented Arabic corpus. | |
| tech,5-3-P03-1058,bq | Our investigation reveals that this <term> | method | of acquiring sense-tagged data </term> is | #4861 Our investigation reveals that thismethod of acquiring sense-tagged data is promising. |
| the <term> algorithms </term> , we present a | method | of <term> HMM training </term> that improves | #5580 Observing that the quality of the lexicon greatly impacts the accuracy that can be achieved by the algorithms, we present a method of HMM training that improves accuracy when training of lexical probabilities is unstable. | |
| this limitation , this paper proposes a | method | utilizing the perceptual groups of <term> | #5658 To overcome this limitation, this paper proposes a method utilizing the perceptual groups of objects and n-ary relations among them. | |
| </term> . Our study reveals that the proposed | method | not only reduces an extensive system development | #5825 Our study reveals that the proposed method not only reduces an extensive system development effort but also improves the transliteration accuracy significantly. | |
| approach </term> . The advantage of this novel | method | is that it clusters all <term> inflected | #6029 The advantage of this novel method is that it clusters all inflected forms of an ambiguous word in one classifier, therefore augmenting the training material available to the algorithm. | |
| tech,3-1-C04-1116,bq | more robust . We present a <term> text mining | method | </term> for finding <term> synonymous expressions | #6097 We present a text mining method for finding synonymous expressions based on the distributional hypothesis in a set of coherent corpora. |
| encouraging results . The paper presents a | method | for <term> word sense disambiguation </term> | #6440 The paper presents a method for word sense disambiguation based on parallel corpora. | |
| </term> and <term> Text Summarisation </term> . Our | method | takes advantage of the different way in | #6959 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. | |
| pronouns </term> . <term> Boosting </term> , the | method | in question , combines the moderately accurate | #7037 Boosting, the method in question, combines the moderately accurate hypotheses of several classifiers to form a highly accurate one. | |
| tech,4-1-H05-1095,bq | phrase-based statistical machine translation | method | </term> , based on <term> non-contiguous phrases | #7345 This paper presents a phrase-based statistical machine translation method, based on non-contiguous phrases, i.e. phrases with gaps. |
| tech,3-1-H05-2007,bq | <term> metrics </term> . We describe a <term> | method | </term> for identifying systematic <term> patterns | #7631 We describe amethod for identifying systematic patterns in translation data using part-of-speech tag sequences. |
| tech,5-3-I05-5003,bq | also introduce a novel <term> classification | method | </term> based on <term> PER </term> which leverages | #8373 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. |
| tech,3-1-I05-5008,bq | in the experiments . We propose a <term> | method | </term> that automatically generates <term> | #8444 We propose amethod that automatically generates paraphrase sets from seed sentences to be used as reference sets in objective machine translation evaluation measures like BLEU and NIST. |
| tech,4-5-J05-1003,bq | </term> into account . We introduce a new <term> | method | </term> for the <term> reranking task </term> | #8763 We introduce a newmethod for the reranking task, based on the boosting approach to ranking problems described in Freund et al. (1998). |
