A Weak-supervision Method for Automating Training Set Creation in Multi-domain Aspect Sentiment Classification

Massimo Ruffolo, Massimo Ruffolo, Francesco Visalli

2020

Abstract

Aspect Based Sentiment Analysis (ABSA) is receiving growing attention from the research community because it has applications in several real world use cases. To train deep learning models for ABSA in vertical domains may result a laborious process requiring a significative human effort in creating proper training sets. In this work we present initial studies regarding the definition of an easy-to-use, flexible, and reusable weakly-supervised method for the Aspect Sentence Classification task of ABSA. Our method mainly consists in a process where templates of Labeling Functions automatically annotate sentences, and then the generative model of Snorkel constructs a probabilistic training set. In order to test effectiveness and applicability of our method we trained machine learning models where the loss function is informed about the probabilistic nature of the labels. In particular, we fine-tuned BERT models on two famous disjoint SemEval datasets related to laptops and restaurants.

Paper Citation

in Harvard Style

Ruffolo M. and Visalli F. (2020). A Weak-supervision Method for Automating Training Set Creation in Multi-domain Aspect Sentiment Classification. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-395-7, pages 249-256. DOI: 10.5220/0009165602490256

in Bibtex Style

@conference{icaart20,
author={Massimo Ruffolo and Francesco Visalli},
title={A Weak-supervision Method for Automating Training Set Creation in Multi-domain Aspect Sentiment Classification},
booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2020},
pages={249-256},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009165602490256},
isbn={978-989-758-395-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - A Weak-supervision Method for Automating Training Set Creation in Multi-domain Aspect Sentiment Classification
SN - 978-989-758-395-7
AU - Ruffolo M.
AU - Visalli F.
PY - 2020
SP - 249
EP - 256
DO - 10.5220/0009165602490256