Results 31 to 40 of about 5,942,306 (303)

Domain-Specific Aspect-Sentiment Pair Extraction Using Rules and Compound Noun Lexicon for Customer Reviews

open access: yesInformatics, 2018
Online reviews are an important source of opinion to measure products’ quality. Hence, automated opinion mining is used to extract important features (aspect) and related comments (sentiment).
Noor Rizvana Ahamed Kabeer   +2 more
doaj   +1 more source

Joint Aspect Extraction and Sentiment Analysis with Directional Graph Convolutional Networks

open access: yesInternational Conference on Computational Linguistics, 2020
End-to-end aspect-based sentiment analysis (EASA) consists of two sub-tasks: the first extracts the aspect terms in a sentence and the second predicts the sentiment polarities for such terms.
Guimin Chen, Yuanhe Tian, Yan Song
semanticscholar   +1 more source

Extracting Customer Reviews from Online Shopping and Its Perspective on Product Design [PDF]

open access: yesVietnam Journal of Computer Science, 2019
This paper presents a study on how we can extract helpful review from customers and its effect on the early phase when designing a product. We present a framework for analyzing the reviews from online shopping sites by detecting helpful reviews, aspects,
Kieu Que Anh   +2 more
doaj   +1 more source

Opinion Triplet Extraction for Aspect-Based Sentiment Analysis Using Co-Extraction Approach

open access: yesJournal of ICT, 2022
In aspect-based sentiment analysis, tasks are diverse and consist of aspect term extraction, aspect categorization, opinion term extraction, sentiment polarity classification, and relation extractions of aspect and opinion terms.
Rifo Ahmad Genadi   +1 more
doaj   +1 more source

Implicit Aspect Extraction from Online Clothing Reviews with Fine-tuning BERT Algorithm

open access: yesJournal of Physics: Conference Series, 2021
In the era of e-commerce, tremendous product reviews can provide quick and valuable insight into the market trends. Aspect-based sentiment analysis (ABSA) on product reviews is becoming increasingly important for both companies and consumers.
Li Yu, Xuefei Bai
semanticscholar   +1 more source

Span-Level Dual-Encoder Model for Aspect Sentiment Triplet Extraction [PDF]

open access: yesJisuanji kexue yu tansuo, 2023
Aspect sentiment triplet extraction (ASTE)  is one of the subtasks of aspect-based sentiment analysis, which aims to identify all aspect terms, their corresponding opinion terms and sentiment polarities in sentences.
ZHANG Yunqi, LI Songda, LAN Yuquan, LI Dongxu, ZHAO Hui
doaj   +1 more source

Aspect Extraction from Bangla Reviews Through Stacked Auto-Encoders

open access: yesData, 2019
Interactions between online users are growing more and more in recent years, due to the latest developments of the web. People share online comments, opinions, and reviews about many topics. Aspect extraction is the automatic process of understanding the
Matteo Bodini
doaj   +1 more source

An Unsupervised Neural Attention Model for Aspect Extraction

open access: yesAnnual Meeting of the Association for Computational Linguistics, 2017
Aspect extraction is an important and challenging task in aspect-based sentiment analysis. Existing works tend to apply variants of topic models on this task. While fairly successful, these methods usually do not produce highly coherent aspects.
Ruidan He   +3 more
semanticscholar   +1 more source

Enhancing Aspect Extraction for Hindi

open access: yesECNLP, 2021
Aspect extraction is not a well-explored topic in Hindi, with only one corpus having been developed for the task. In this paper, we discuss the merits of the existing corpus in terms of quality, size, sparsity, and performance in aspect extraction tasks ...
Arghya Bhattacharya   +2 more
semanticscholar   +1 more source

Aspect-Oriented Sentiment Analysis: A Topic Modeling-Powered Approach

open access: yesJournal of Intelligent Systems, 2018
Because of exponential growth in the number of people who purchase products online, e-commerce organizations are vying for each other to offer innovative and improved services to its customers.
Anoop V.S., Asharaf S.
doaj   +1 more source

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