A multi-scale local attention mechanism for aspect extraction [PDF]
Scientific ReportsAspect extraction is a critical step in constructing knowledge graphs and involves extracting aspect information from unstructured text. Current methods typically employ attention-based techniques such as global or local attention mechanisms, each with ...
Qian Yang +7 more
doaj +2 more sources
Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations [PDF]
arXiv.org, 2023 Existing aspect extraction methods mostly rely on explicit or ground truth aspect information, or using data mining or machine learning approaches to extract aspects from implicit user feedback such as user reviews.
Pan Li +3 more
semanticscholar +1 more source
Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs [PDF]
International Conference on Information and Knowledge Management, 2022 The extraction of aspect terms is a critical step in fine-grained sentiment analysis of text. Existing approaches for this task have yielded impressive results when the training and testing data are from the same domain.
Phillip Howard +7 more
semanticscholar +1 more source
DILBERT: Customized Pre-Training for Domain Adaptation with Category Shift, with an Application to Aspect Extraction [PDF]
Conference on Empirical Methods in Natural Language Processing, 2021 The rise of pre-trained language models has yielded substantial progress in the vast majority of Natural Language Processing (NLP) tasks. However, a generic approach towards the pre-training procedure can naturally be sub-optimal in some cases ...
Entony Lekhtman +2 more
semanticscholar +1 more source
NOVEL MULTI-LEVEL ASPECT BASED SENTIMENT ANALYSIS FOR IMPROVED ROOT-CAUSE ANALYSIS
ICTACT Journal on Soft Computing, 2021 Aspect extraction and sentiment identification are the two important tasks to provide effective root cause analysis. This work presents a Multi-Level Aspect based Sentiment Analysis (MLASA) model that integrates the aspect extraction and sentiment ...
Naveenkumar Seerangan +1 more
doaj +1 more source
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2023 Social Media has revolutionized how individuals, groups, and communities interact. This immense quantity of unstructured data holds valuable information expressed in informal language.
Julia da Rocha Junqueira +6 more
doaj +1 more source
Arabic Aspect Extraction Based on Stacked Contextualized Embedding With Deep Learning
IEEE Access, 2022 The exponential growth of the internet and a multi-fold increase in social media users in the last decade have resulted in a massive growth of unstructured data.
Arwa S. Fadel, M. Saleh, O. Abulnaja
semanticscholar +1 more source
A Joint Model for Extracting Latent Aspects and Their Ratings From Online Employee Reviews
Frontiers in Physics, 2022 The personal description of a company associated with job satisfaction, company culture, and opinions of senior leadership is available on workplace community websites.
Zhuo-Ming Ren +3 more
doaj +1 more source
A Systematic Mapping Study of the Empirical Explicit Aspect Extractions in Sentiment Analysis
IEEE Access, 2020 Aspect-based sentiment analysis (ABSA) is described as one of the most vibrant research areas over the last decade. However, due to the exponential increase in aspect-based sentiment researches, there is a massive interest in advanced explicit aspect ...
Jaafar Zubairu Maitama +2 more
doaj +1 more source
LISA: Language-Independent Method for Aspect-Based Sentiment Analysis
IEEE Access, 2020 Understanding “what others think” is one of the most eminent pieces of knowledge in the decision-making process required in a wide spectrum of applications. The procedure of obtaining knowledge from each aspect (property) of users' opinions
Mohammadreza Shams +2 more
doaj +1 more source