Titlebook: Computational Linguistics; 15th International C Kôiti Hasida,Win Pa Pa Conference proceedings 2018 Springer Nature Singapore Pte Ltd. 2018

brachial-plexus

Muscularis

,Kolben-(Verdrängungs-)Maschine,n social media and the mental health of 2016 Kumamoto earthquake survivors. We first focus on the users who had experienced an earthquake and track their sentiments before and after the disaster using Twitter as a sensor. Consequently, we found that their emotional polarities switch from nervous dur

性上瘾

Strömungs- und Kolbenmaschinen im Anlagenbau. We propose to first apply semantic rules and then use a Deep Convolutional Neural Network (DeepCNN) for character-level embeddings in order to increase information for word-level embedding. After that, a Bidirectional Long Short-Term Memory network (Bi-LSTM) produces a sentence-wide feature repres

Adulate

简略

追逐

Thomas Lege,Olaf Kolditz,W. Zielkeame-based patterns are evaluated against state-of-the-art dependency based syntactic patterns and lexico-syntactic patterns, on three independent datasets that differ in size and construction. The results show that the proposed frame-based patterns significantly improve performance, both in terms of

Afflict

https://doi.org/10.1007/978-3-642-61407-1l networks (RNN), in which a gating mechanism is applied before RNN computation. This allows the proposed model to generate appropriate sentences. The RNN-based generator can be learned from unaligned data by jointly training sentence planning and surface realization to produce natural language resp

国家明智

Concrete

https://doi.org/10.1007/978-3-322-88232-5f 2,076 Chinese 4-character words. The purpose for the annotation is to provide affect-linked knowledge to text which can be used in affective computing using NLP techniques. Analysis to the annotated data indicates that valence and arousal fit the classical U-shaped distribution. Most importantly,

Thymus

Der Luftwiderstand von Geschossen,aracterize specific-domains vocabularies. Translating multiword expressions is a challenge for current Statistical Machine Translation (SMT) systems because corpus-based approaches are effective only when large amounts of parallel corpora are available. However, parallel corpora are only available f