Results 271 to 280 of about 144,225 (306)

Multi-source data fusion for aspect-level sentiment classification

Knowledge-Based Systems, 2020
Abstract Neural networks have achieved great success in aspect-level sentiment classification due to their ability to learn sentiment knowledge from text. Generally, the effectiveness of neural networks relies on sufficiently large training corpora. However, existing aspect-level corpora are relatively small, which greatly limits the performance of ...
Fang Chen, Zhigang Yuan, Yongfeng Huang 0001   +2 more
openaire   +1 more source

Aspect-Level Sentiment Classification with Conv-Attention Mechanism

2018
The aim of aspect-level sentiment classification is to identify the sentiment polarity of a sentence about a target aspect. Existing methods model the context sequence with recurrent network and employ attention mechanism to generate aspect-specific representations.
Qian Yi, Jie Liu 0028, Guixuan Zhang, Shuwu Zhang   +3 more
openaire   +1 more source

An LSTM-CNN attention approach for aspect-level sentiment classification

Journal of Computational Methods in Sciences and Engineering, 2019
Opinions in complex reviews often vary on different aspects of a thing. Coarse-grained sentiment analysis on a sentence can’t capture the sentiment polarity of it accurately. Therefore, aspect-level sentiment classification is a better choice because it is a fine-grained task in sentiment analysis.
Ming Jiang 0009, Wen Zhang, Min Zhang 0029, Jianping Wu, Tao Wen   +4 more
openaire   +1 more source

Revising Attention with Position for Aspect-Level Sentiment Classification

2019
As a fine-grained classification task, aspect-level sentiment classification aims at determining the sentiment polarity given a particular target in a sentence. The key point of this task is to distinguish target-related words and target-unrelated words. To this end, attention mechanism is introduced into this task, which assigns high attention weights
Dong Wang 0029, Tingwen Liu, Bin Wang 0004   +2 more
openaire   +1 more source

Aspect-level Sentiment Classification with HEAT (HiErarchical ATtention) Network

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017
Aspect-level sentiment classification is a fine-grained sentiment analysis task, which aims to predict the sentiment of a text in different aspects. One key point of this task is to allocate the appropriate sentiment words for the given aspect.Recent work exploits attention neural networks to allocate sentiment words and achieves the state-of-the-art ...
Jiajun Cheng, Shenglin Zhao, Jiani Zhang 0001, Irwin King, Xin Zhang 0018, Hui Wang 0030   +5 more
openaire   +1 more source

Aspect Level Sentiment Classification Based on Double Attention Mechanism

Proceedings of the 2019 2nd International Conference on E-Business, Information Management and Computer Science, 2019
Aspect sentiment classification is a fine-grained sentiment classification method, which is used to identify the sentimental polarity of a given aspect word in one sentence. Among the existing aspect-level sentiment classification methods, the deep learning model with the attention mechanism solves the problem of key word recognition in sentiment ...
Cui Zhang, Maojie Zhou
openaire   +1 more source

A Position-aware Transformation Network for Aspect-level Sentiment Classification

2019 International Joint Conference on Neural Networks (IJCNN), 2019
This paper introduce a novel Position-aware Transformation Network (PTNet) for aspect-level sentiment classification. On the one hand, attention mechanisms have been employed to model the relationship between aspect and context. However, the position information of aspect words is rarely emphasized for sentiment prediction.
Tao Jiang 0059, Jiahai Wang, Youwei Song, Yanghui Rao   +3 more
openaire   +1 more source

Dependency Parsing and Attention Network for Aspect-Level Sentiment Classification

2018
Aspect-level sentiment classification aims to determine the sentiment polarity of the sentence towards the aspect. The key element of this task is to characterize the relationship between the aspect and the contexts. Some recent attention-based neural network methods regard the aspect as the attention calculation goal, so they can learn the association
Zhifan Ouyang, Jindian Su
openaire   +1 more source

Surrounding-Based Attention Networks for Aspect-Level Sentiment Classification

2019
Aspect-level sentiment classification aims to identify the polarity of a target word in a sentence. Studies on sentiment classification have found that a target’s surrounding words have great impacts and global attention to the target. However, existing neural-network-based models either depend on expensive phrase-level annotation or do not fully ...
Yueheng Sun, Xianchen Wang, Hongtao Liu, Wenjun Wang 0002, Pengfei Jiao   +4 more
openaire   +1 more source

Aspect-Level Sentiment Classification with Dependency Rules and Dual Attention

2019
Aspect-level sentiment classification aims to predict the sentiment polarity towards the given aspects of sentences. Neural network models with attention mechanism have achieved great success in this area. However, existing methods fail to capture enough aspect information. Besides, it is hard for simple attention mechanism to model complex interaction
Yunkai Yang, Tieyun Qian, Zhuang Chen 0002   +2 more
openaire   +1 more source