Results 11 to 20 of about 583,468 (318)

Aspect term extraction for sentiment analysis in large movie reviews using Gini Index feature selection method and SVM classifier [PDF]

open access: bronze, 2016
With the rapid development of the World Wide Web, electronic word-of-mouth interaction has made consumers active participants. Nowadays, a large number of reviews posted by the consumers on the Web provide valuable information to other consumers.
Asha, S.Manek.   +3 more
core   +3 more sources

Aspect Term Extraction with History Attention and Selective Transformation [PDF]

open access: goldProceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
Aspect Term Extraction (ATE), a key sub-task in Aspect-Based Sentiment Analysis, aims to extract explicit aspect expressions from online user reviews. We present a new framework for tackling ATE. It can exploit two useful clues, namely opinion summary and aspect detection history.
Xin Li   +4 more
openalex   +3 more sources

Progressive Self-Training with Discriminator for Aspect Term Extraction [PDF]

open access: hybridProceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021
Qianlong Wang   +4 more
openalex   +2 more sources

ATE_ABSITA @ EVALITA2020: Overview of the Aspect Term Extraction and Aspect-based Sentiment Analysis Task [PDF]

open access: hybrid, 2020
Over the last years, the rise of novel sentiment analysis techniques to assess aspect-based opinions on product reviews has become a key component for providing valuable insights to both consumers and businesses. To this extent, we propose ATE_ABSITA: the EVALITA 2020 shared task on Aspect Term Extraction and Aspect-Based Sentiment Analysis.
Lorenzo De Mattei   +5 more
openalex   +5 more sources

A Semi-Supervised Approach for Aspect Category Detection and Aspect Term Extraction from Opinionated Text [PDF]

open access: diamondComputers, Materials & Continua, 2023
The Internet has become one of the significant sources for sharing information and expressing users' opinions about products and their interests with the associated aspects. It is essential to learn about product reviews; however, to react to such reviews, extracting aspects of the entity to which these reviews belong is equally important. Aspect-based
Bishrul Haq   +4 more
openalex   +4 more sources

Comprehensive analysis of aspect term extraction methods using various text embeddings [PDF]

open access: bronzeComputer Speech & Language, 2021
Recently, a variety of model designs and methods have blossomed in the context of the sentiment analysis domain. However, there is still a lack of wide and comprehensive studies of aspect-based sentiment analysis (ABSA). We want to fill this gap and propose a comparison with ablation analysis of aspect term extraction using various text embedding ...
Łukasz Augustyniak   +2 more
openalex   +4 more sources

Aspect and Opinion Term Extraction Using Graph Attention Network [PDF]

open access: green
In this work we investigate the capability of Graph Attention Network for extracting aspect and opinion terms. Aspect and opinion term extraction is posed as a token-level classification task akin to named entity recognition. We use the dependency tree of the input query as additional feature in a Graph Attention Network along with the token and part ...
Abir Chakraborty
openalex   +3 more sources

Aspect Term Extraction Using Deep Learning Model with Minimal Feature Engineering [PDF]

open access: greenAdvanced Information Systems Engineering32nd International Conference, 2020
Zschornack Rodrigues Saraiva F   +2 more
europepmc   +3 more sources

Generating Complement Data for Aspect Term Extraction with GPT-2 [PDF]

open access: goldProceedings of the Third Workshop on Deep Learning for Low-Resource Natural Language Processing, 2022
Amir Pouran Ben Veyseh   +2 more
openalex   +2 more sources

An ensemble approach for aspect term extraction in Turkish texts

open access: diamondPamukkale University Journal of Engineering Sciences, 2022
Mehmet Umut Salur   +2 more
openalex   +3 more sources

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