Results 21 to 30 of about 14,029 (259)
Semi-Supervised Model for Aspect Sentiment Detection
Information, 2023 Advancements in text representation have produced many deep language models (LMs), such as Word2Vec and recurrent-based LMs. However, there are scarce works that focus on detecting implicit sentiments with a small amount of labelled data because there ...
Zohreh Madhoushi +2 more
doaj +1 more source
Adaptive Local Context and Syntactic Feature Modeling for Aspect-Based Sentiment Analysis
Applied Sciences, 2023 Aspect-based sentiment analysis is a fine-grained sentiment analysis task that consists of two types of subtasks: aspect term extraction and aspect sentiment classification. In the aspect term extraction task, current methods suffer from the lack of fine-
Jie Huang, Yunpeng Cui, Shuo Wang
doaj +1 more source
Applied Sciences, 2023 Most of the aspect-based sentiment analysis research completes the two subtasks (aspect terms extraction and aspect sentiment classification) separately, and it cannot see the full picture and actual effect of the complete aspect-based sentiment analysis.
Musheng Chen +3 more
doaj +1 more source
ASPECT-BASED SENTIMENT ANALYSIS METHODS IN RECENT YEARS
Asia-Pacific Journal of Information Technology and Multimedia, 2019 Sentiment Analysis (SA) is the computational treatment of opinions, sentiments and subjectivity of text. Aspect-based Sentiment Analysis (ABSA) is a specific SA that aims to extract most important aspects of an entity and predict the polarity of each ...
Zohreh Madhoushi +2 more
doaj +1 more source
Aspect-based Sentiment Analysis Based on Dual-channel Graph Convolutional Network with Sentiment Knowledge [PDF]
Jisuanji kexue, 2023 Aspect-based sentiment analysis is a fine-grained sentiment analysis task whose goal is to classify the sentiment polarity of the given aspect terms in a sentence.Most of the current sentiment classification models build a graph neural network on the ...
YANG Ying, ZHANG Fan, LI Tianrui
doaj +1 more source
Attention-based Sentiment Reasoner for aspect-based sentiment analysis [PDF]
Human-centric Computing and Information Sciences, 2019 AbstractAspect-based sentiment analysis (ABSA) is a powerful way of predicting the sentiment polarity of text in natural language processing. However, understanding human emotions and reasoning from text like a human continues to be a challenge. In this paper, we propose a model, named Attention-based Sentiment Reasoner (AS-Reasoner), to alleviate the ...
Ning Liu 0027 +4 more
openaire +2 more sources
Aspect based sentiment analysis [PDF]
, 2021 Τα συστήματα Ανάλυσης Συναισθήματος Βασισμένης σε Χαρακτηριστικά (Aspect Based Sentiment Analysis, ABSA) δέχονται ως είσοδο ένα σύνολο κειμένων (π.χ. κριτικές προϊόντων ή μηνύματα κοινωνικών δικτύων) που σχολιάζουν μια συγκεκριμένη οντότητα (π.χ. ένα συγκεκριμένο μοντέλου κινητού τηλεφώνου). Επιχειρούν να εντοπίσουν τα κυριότερα (π.χ.
openaire +1 more source
Zero-Shot Aspect-Based Sentiment Analysis
CoRR, 2022 Aspect-based sentiment analysis (ABSA) typically requires in-domain annotated data for supervised training/fine-tuning. It is a big challenge to scale ABSA to a large number of new domains. This paper aims to train a unified model that can perform zero-shot ABSA without using any annotated data for a new domain.
Lei Shu 0004 +3 more
openaire +3 more sources
Deep learning-based application for multilevel sentiment analysis of Indonesian hotel reviews
Heliyon, 2023 Purpose: In this study, we present a web-based application that retrieves hotel review documents in Indonesian languages from an online travel agent (OTA) and analyses their sentiments from the coarse-grained document to the fine-grained aspect level ...
Retno Kusumaningrum +4 more
doaj +1 more source
Towards Generative Aspect-Based Sentiment Analysis [PDF]
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), 2021 Aspect-based sentiment analysis (ABSA) has received increasing attention recently. Most existing work tackles ABSA in a discriminative manner, designing various task-specific classification networks for the prediction. Despite their effectiveness, these methods ignore the rich label semantics in ABSA problems and require extensive task-specific designs.
Wenxuan Zhang 0001 +4 more
openaire +2 more sources