A Joint Model for Aspect-Category Sentiment Analysis with Contextualized Aspect Embedding

by   Yuncong Li, et al.

Aspect-category sentiment analysis (ACSA) aims to identify all the aspect categories mentioned in the text and their corresponding sentiment polarities. Some joint models have been proposed to address this task. However, these joint models do not solve the following two problems well: mismatching between the aspect categories and the sentiment words, and data deficiency of some aspect categories. To solve them, we propose a novel joint model which contains a contextualized aspect embedding layer and a shared sentiment prediction layer. The contextualized aspect embedding layer extracts the aspect category related information, which is used to generate aspect-specific representations for sentiment classification like traditional context-independent aspect embedding (CIAE) and is therefore called contextualized aspect embedding (CAE). The CAE can mitigate the mismatching problem because it is semantically more related to sentiment words than CIAE. The shared sentiment prediction layer transfers sentiment knowledge between aspect categories and alleviates the problem caused by data deficiency. Experiments conducted on SemEval 2016 Datasets show that our proposed model achieves state-of-the-art performance.



page 1

page 2

page 3

page 4


Sentence Constituent-Aware Aspect-Category Sentiment Analysis with Graph Attention Networks

Aspect category sentiment analysis (ACSA) aims to predict the sentiment ...

A Multi-Task Incremental Learning Framework with Category Name Embedding for Aspect-Category Sentiment Analysis

(T)ACSA tasks, including aspect-category sentiment analysis (ACSA) and t...

Scalable End-to-End Training of Knowledge Graph-Enhanced Aspect Embedding for Aspect Level Sentiment Analysis

Aspect level sentiment classification (ALSC) is a difficult problem with...

ASAP: A Chinese Review Dataset Towards Aspect Category Sentiment Analysis and Rating Prediction

Sentiment analysis has attracted increasing attention in e-commerce. The...

Explaining a Neural Attention Model for Aspect-Based Sentiment Classification Using Diagnostic Classification

Many high performance machine learning models for Aspect-Based Sentiment...

Learning to Attend via Word-Aspect Associative Fusion for Aspect-based Sentiment Analysis

Aspect-based sentiment analysis (ABSA) tries to predict the polarity of ...

Context-aware Embedding for Targeted Aspect-based Sentiment Analysis

Attention-based neural models were employed to detect the different aspe...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.