Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment Classification

08/30/2019
by   Alexander Rietzler, et al.
0

Aspect-Target Sentiment Classification (ATSC) is a subtask of Aspect-Based Sentiment Analysis (ABSA), which has many applications e.g. in e-commerce, where data and insights from reviews can be leveraged to create value for businesses and customers. Recently, deep transfer-learning methods have been applied successfully to a myriad of Natural Language Processing (NLP) tasks, including ATSC. Building on top of the prominent the BERT language model, we approach ATSC by using a two-step procedure: Self-supervised domain-specific BERT language model finetuning, followed by supervised task-specific finetuning. Our findings on how to best exploit domain-specific language model finetuning enables us to produce new state-of-the-art performance on the SemEval 2014 Task 4 restaurants dataset. In addition, to explore the real-world robustness of our models, we perform cross-domain evaluation. We show that a cross-domain adapted BERT language model performs significantly better compared to strong baseline models like vanilla BERT-base and XLNet-base.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/28/2020

DomBERT: Domain-oriented Language Model for Aspect-based Sentiment Analysis

This paper focuses on learning domain-oriented language models driven by...
research
03/05/2021

Fine-tuning Pretrained Multilingual BERT Model for Indonesian Aspect-based Sentiment Analysis

Although previous research on Aspect-based Sentiment Analysis (ABSA) for...
research
08/03/2021

Exploiting BERT For Multimodal Target Sentiment Classification Through Input Space Translation

Multimodal target/aspect sentiment classification combines multimodal se...
research
11/29/2020

Coarse-to-Fine Memory Matching for Joint Retrieval and Classification

We present a novel end-to-end language model for joint retrieval and cla...
research
12/21/2020

Cross-domain Retrieval in the Legal and Patent Domains: a Reproducibility Study

Domain specific search has always been a challenging information retriev...
research
08/02/2023

Bio+Clinical BERT, BERT Base, and CNN Performance Comparison for Predicting Drug-Review Satisfaction

The objective of this study is to develop natural language processing (N...
research
10/27/2019

Thieves on Sesame Street! Model Extraction of BERT-based APIs

We study the problem of model extraction in natural language processing,...

Please sign up or login with your details

Forgot password? Click here to reset