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

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Klaus-Jürgen Peschges,Steffen Manserstudy, in order to further explore this topic, we present an alternative approach to Khmer POS tagging using Conditional Random Fields (CRFs). Since the features greatly affect the tagging accuracy, we investigate five groups of features and use them with the CRF model. First, we study different con

组成

Strömungskupplungen und Strömungswandlerethods are applied prevalently in practice. These are inconsistent and complicated in some cases, due to unstable phonemic, orthographic, and etymological principles. Consequently, statistical approaches are required for the task. We collect and manually align 7, 658 Khmer name Romanization instance

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身心疲惫

A Deep Neural Architecture for Sentence-Level Sentiment Classification in Twitter Social Networking. 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

amputation

Learning Word Embeddings for Aspect-Based Sentiment Analysisom an unannotated corpus and they are independent from their applications. In this paper we aim to enrich the word vectors by adding more information derived from an application of them which is the aspect based sentiment analysis. We propose a new model using a combination of unsupervised and super

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