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Stance Classification with Target-specific Neural Attention
TLDR
We propose a neural network-based model, which incorporates target-specific information into stance classification by following a novel attention mechanism to locate critical parts of text which are related to target. Expand
Event-Driven Emotion Cause Extraction with Corpus Construction
TLDR
We propose a new event-driven emotion cause extraction method using multi-kernel SVMs where a syntactical tree based approach is used to represent events in text. Expand
A Question Answering Approach for Emotion Cause Extraction
TLDR
We propose a deep memory network architecture to model the context of each word in different memory slots to model context information. Expand
Emotion Cause Extraction, A Challenging Task with Corpus Construction
TLDR
In this paper, we present a new challenging task for emotion analysis called emotion cause extraction. Expand
A Mixed Model for Cross Lingual Opinion Analysis
TLDR
We propose a mixed CLOA model, which estimates the confidence of each monolingual opinion analysis system by using their training errors through bilingual transfer self-training and co-training, respectively. Expand
Overview of NLPCC Shared Task 4: Stance Detection in Chinese Microblogs
TLDR
This paper presents the overview of the shared task, stance detection in Chinese microblogs, in NLPCC-ICCPOL 2016. Expand
Disease named entity recognition by combining conditional random fields and bidirectional recurrent neural networks
TLDR
The recognition of disease and chemical named entities in scientific articles is a very important subtask in information extraction in the biomedical domain. Expand
Emotion Cause Detection with Linguistic Construction in Chinese Weibo Text
TLDR
In this paper, an emotion cause annotated corpus on Chinese Weibo text is designed and annotated. Expand
Cross-lingual Opinion Analysis via Negative Transfer Detection
TLDR
We propose a novel method in transductive transfer learning to identify noises through the detection of negative transfers. Expand
Convolution-Based Neural Attention With Applications to Sentiment Classification
TLDR
We propose to use convolution operation to simulate attentions and give a mathematical explanation of our neural attention model to build a hierarchical sentiment classification model. Expand
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