| size of the <term> databases </term> used some | results | about the effectiveness of these <term> indices | #195 Despite the small size of the databases used some results about the effectiveness of these indices can be obtained. | ||
| industry watch function . We also report | results | of a preliminary , <term> qualitative user | #347 We also report results of a preliminary, qualitative user evaluation of the system, which while broadly positive indicates further work needs to be done on the interface to make users aware of the increased potential of IE-enhanced text browsers. | ||
| </term> at which they made this decision . The | results | of this experiment , along with a preliminary | #756 The results of this experiment, along with a preliminary analysis of the factors involved in the decision making process will be presented here. | ||
| reference </term> . We provide experimental | results | that clearly show the need for a <term> dynamic | #1134 We provide experimental results that clearly show the need for a dynamic language model combination to improve the performance further. | ||
| suitable <term> superset </term> of L . The | results | of a practical evaluation of this method | #1737 The results of a practical evaluation of this method on a wide coverage English grammar are given. | ||
| answering </term> which is based on combining the | results | from different <term> answering agents </term> | #2341 Motivated by the success of ensemble methods in machine learning and other areas of natural language processing, we developed a multi-strategy and multi-source approach to question answering which is based on combining the results from different answering agents searching for answers in multiple corpora. | ||
| resolution algorithm </term> that combines | results | from the <term> answering agents </term> at | #2382 We present our multi-level answer resolution algorithm that combines results from the answering agents at the question, passage, and/or answer levels. | ||
| <term> word-based models </term> . Our empirical | results | , which hold for all examined <term> language | #2591 Our empirical results, which hold for all examined language pairs, suggest that the highest levels of performance can be obtained through relatively simple means: heuristic learning of phrase translations from word-based alignments and lexical weighting of phrase translations. | ||
| error rate </term> , and provide evaluation | results | involving <term> automatic extraction </term> | #2774 We present an implementation of the model based on finite-state models, demonstrate the model's ability to significantly reduce character and word error rate, and provide evaluation results involving automatic extraction of translation lexicons from printed text. | ||
| </term> . Using these ideas together , the | resulting | <term> tagger </term> gives a 97.24 % <term> | #2986 Using these ideas together, the resulting tagger gives a 97.24% accuracy on the Penn Treebank WSJ, an error reduction of 4.4% on the best previous single automatically learned tagging result. | ||
| other,30-2-N03-1033,ak | single <term> automatically learned tagging | result | </term> . Sources of <term> training data </term> | #3013 Using these ideas together, the resulting tagger gives a 97.24% accuracy on the Penn Treebank WSJ, an error reduction of 4.4% on the best previous single automatically learned tagging result. | |
| two different <term> algorithms </term> . The | results | show that it can provide a significant | #3273 The results show that it can provide a significant improvement in alignment quality. | ||
| tagged by the first <term> learner </term> . The | resulting | <term> NE system </term> approaches <term> supervised | #3378 The resulting NE system approaches supervised NE performance for some NE types. | ||
| word alignment </term> . We show experimental | results | on <term> block selection criteria </term> | #3465 We show experimental results on block selection criteria based on unigram counts and phrase length. | ||
| decision tree learning </term> . The experimental | results | prove our claim that accurate <term> predicate-argument | #3776 The experimental results prove our claim that accurate predicate-argument structures enable high quality IE results. | ||
| tech,13-4-P03-1002,ak | structures </term> enable high quality <term> IE | results | </term> . This paper proposes the <term> Hierarchical | #3788 The experimental results prove our claim that accurate predicate-argument structures enable high quality IE results. | |
| </term> and a <term> kernel function </term> . The | results | of the experiments demonstrate that the | #3866 The results of the experiments demonstrate that the HDAG Kernel is superior to other kernel functions and baseline methods. | ||
| expanded <term> stop lists </term> . Experimental | results | validate our hypothesis . This paper concerns | #4122 Experimental results validate our hypothesis. | ||
| other,5-3-P03-1031,ak | candidates </term> for the <term> understanding | result | </term> can be obtained for a <term> user utterance | #4162 Since multiple candidates for the understanding result can be obtained for a user utterance due to the ambiguity of speech understanding, it is not appropriate to decide on a single understanding result after each user utterance. | |
| other,31-3-P03-1031,ak | to decide on a single <term> understanding | result | </term> after each <term> user utterance </term> | #4188 Since multiple candidates for the understanding result can be obtained for a user utterance due to the ambiguity of speech understanding, it is not appropriate to decide on a single understanding result after each user utterance. |
