تقرير
Compositional Sentence Representation from Character within Large Context Text
| العنوان: | Compositional Sentence Representation from Character within Large Context Text |
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| المؤلفون: | Kim, Geonmin, Lee, Hwaran, Choi, Jisu, Lee, Soo-young |
| سنة النشر: | 2016 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language |
| الوصف: | This paper describes a Hierarchical Composition Recurrent Network (HCRN) consisting of a 3-level hierarchy of compositional models: character, word and sentence. This model is designed to overcome two problems of representing a sentence on the basis of a constituent word sequence. The first is a data-sparsity problem in word embedding, and the other is a no usage of inter-sentence dependency. In the HCRN, word representations are built from characters, thus resolving the data-sparsity problem, and inter-sentence dependency is embedded into sentence representation at the level of sentence composition. We adopt a hierarchy-wise learning scheme in order to alleviate the optimization difficulties of learning deep hierarchical recurrent network in end-to-end fashion. The HCRN was quantitatively and qualitatively evaluated on a dialogue act classification task. Especially, sentence representations with an inter-sentence dependency are able to capture both implicit and explicit semantics of sentence, significantly improving performance. In the end, the HCRN achieved state-of-the-art performance with a test error rate of 22.7% for dialogue act classification on the SWBD-DAMSL database. Comment: 13pages |
| نوع الوثيقة: | Working Paper |
| الوصول الحر: | http://arxiv.org/abs/1605.00482Test |
| رقم الانضمام: | edsarx.1605.00482 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |