| large database of TV shows . Emotions and | other | <term> indices </term> such as the dominance | #165 Emotions and other indices such as the dominance distribution of speakers might be available on the surface and could be used directly. | ||
| were <term> expert human translations </term> , | others | were <term> machine translation outputs </term> | #706 Some of the extracts were expert human translations, others were machine translation outputs. | ||
| alternative markers </term> , which includes | other | ( than ) , such ( as ) , and besides . | #1834 This paper presents a formal analysis for a large class of words called alternative markers, which includes other (than), such (as), and besides. | ||
| </term> in <term> machine learning </term> and | other | areas of <term> natural language processing | #2318 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. | ||
| primarily knowledge-based mechanisms and the | other | adopting statistical techniques . We present | #2368 The answering agents adopt fundamentally different strategies, one utilizing primarily knowledge-based mechanisms and the other adopting statistical techniques. | ||
| , and gives them translingual reach into | other | <term> languages </term> by leveraging <term> | #3628 It gives users the ability to spend their time finding more data relevant to their task, and gives them translingual reach into other languages by leveraging human language technology. | ||
| the <term> HDAG Kernel </term> is superior to | other | <term> kernel functions </term> and <term> baseline | #3878 The results of the experiments demonstrate that the HDAG Kernel is superior to other kernel functions and baseline methods. | ||
| described generalize naturally to NLP structures | other | than <term> parse trees </term> . This paper | #5576 Although our experiments are focused on parsing, the techniques described generalize naturally to NLP structures other than parse trees. | ||
| <term> errors </term> are analyzed in detail . | Other | tasks using the method developed for <term> | #6195 The few errors are analyzed in detail. Other tasks using the method developed for ILIMP are described briefly, as well as the use of ILIMP in a modular syntactic analysis system. | ||
| classification accuracy </term> over all of the | other | models used in the experiments . Towards | #7484 Our technique gives a substantial improvement in paraphrase classification accuracy over all of the other models used in the experiments. | ||
| of integrating some kind of information | other | than <term> grammar </term> sensu stricto into | #7841 Moreover, some examples are given that underline the necessity of integrating some kind of information other than grammar sensu stricto into the treebank. | ||
| the approach should be applicable to many | other | <term> NLP problems </term> which are naturally | #8323 Although the experiments in this article are on natural language parsing (NLP), the approach should be applicable to many other NLP problems which are naturally framed as ranking tasks, for example, speech recognition, machine translation, or natural language generation. | ||
| they are <term> translations </term> of each | other | . Using this approach , we extract <term> | #8387 We train a maximum entropy classifier that, given a pair of sentences, can reliably determinewhether or not they are translations of each other. | ||
| sentence-aligned parallel corpus </term> . All | other | resources are monolingual . We also refer | #10594 All other resources are monolingual. | ||
| strengths and weaknesses , and to compare it to | other | <term> MT systems </term> . Using this <term> | #10714 The method allows a user to explore a model of syntax-based statistical machine translation (MT), to understand the model's strengths and weaknesses, and to compare it to other MT systems. | ||
| co-occurrences </term> . This approach differs from | other | approaches to <term> WSI </term> in that it | #11077 This approach differs from other approaches to WSI in that it enhances the effect of the one sense per collocation observation by using triplets of words instead of pairs. | ||
| show that it is competitive to the best | other | <term> strategies </term> . We introduce a | #11799 We also introduce a new strategy, called Begin/After tagging or BIA, and show that it is competitive to the best other strategies. | ||
| clustering based approach </term> outperforms the | other | <term> clustering methods </term> . This paper | #12325 Experiment results on ACE corpora show that this spectral clustering based approach outperforms the other clustering methods. | ||
| will be unable to correct it at all ; at | other | times , correction will be possible , but | #13915 Ideally, such a parser will correct the deviant input: sometimes, it will be unable to correct it at all; at other times, correction will be possible, but only to within a range of ambiguous possibilities. | ||
| e.g. , <term> newspaper stories </term> and | other | edited texts . However , a great deal of | #14259 Most large text-understanding systems have been designed under the assumption that the input text will be in reasonably neat form, e.g., newspaper stories and other edited texts. |
