نتایج جستجو برای: textual
تعداد نتایج: 21284 فیلتر نتایج به سال:
Music is sound: audible, unique, ephemeral. For music composed before the advent of electronic recording a century and quarter ago, musical texts — unique arrangements symbols by which represented in visible form are our principal evidence for how that sounded when it was created. But Western past preserved not necessarily accurate representations they record. Although make up notation have rem...
the benefits of textual input enhancement in the acquisition of linguistic forms have produced mixed results in sla literature. the present study investigates the effects of textual enhancement on adult foreign language intake of two english linguistic forms-subjunctive mood and inversion structures-to explore the role of the type of linguistic items in input enhancement studies. it also invest...
This paper analyses the contribution of shallow syntactic matching and thesaurus based equivalence in determining semantic equivalence of a pair of sentences. The performance of this approach is evaluated on two data sets and compared to other systems, as well as to manual evaluation results. We conclude that shallow semantics can model equivalence and entailment for pairs of syntactically simi...
We present our experiments on Recognizing Textual Entailment based on modeling the entailment relation as a classification problem. As features used to classify the entailment pairs we use a symmetric similarity measure and a non-symmetric similarity measure. Our system achieved an accuracy of 66% on the RTE-3 development dataset (with 10-fold cross validation) and accuracy of 63% on the RTE-3 ...
The textual entailment system determines whether one sentence can entail another in a common sense. We proposed several approaches to train textual entailment classifiers, including setting ancestor distance threshold, expanding training corpus, using different sets of features, and tuning classifier settings. The results show that a MC classifier trained by using an expanded training corpus an...
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