Automatic Aspect Extraction from Scientific Texts
International Joint Conference on the Analysis of Images, Social Networks and Texts, 2023 Being able to extract from scientific papers their main points, key insights, and other important information, referred to here as aspects, might facilitate the process of conducting a scientific literature review. Therefore, the aim of our research is to create a tool for automatic aspect extraction from Russian-language scientific texts of any domain.
Anna Marshalova +2 more
openaire +3 more sources
Ensemble BiLSTM: A Novel Approach for Aspect Extraction From Online Text
IEEE AccessAspect extraction poses a significant challenge in Natural Language Processing (NLP). Extracting explicit and implicit aspects from online text data remains an ongoing challenge despite significant research efforts.
Mikail Muhammad Azman Busst +4 more
doaj +2 more sources
Multi-Domain Aspect Extraction Using Bidirectional Encoder Representations From Transformers
IEEE Access, 2021 Deep learning and neural language models have obtained state-of-the-art results in aspects extraction tasks, in which the objective is to automatically extract characteristics of products and services that are the target of consumer opinion.
Brucce Neves Dos Santos +2 more
doaj +2 more sources
Deep2s: Improving Aspect Extraction in Opinion Mining With Deep Semantic Representation
IEEE Access, 2020 Syntactical rule based approaches for aspect extraction, which are free from expensive manual annotation, are promising in practice. These approaches extract aspects mainly through the dependency relations in the surface sentence structures.
Xuelian Li +6 more
doaj +2 more sources
Aspect-level multimodal sentiment analysis model based on multi-scale feature extraction [PDF]
Scientific ReportsIn existing multimodal sentiment analysis methods, only the last layer output of BERT is typically used for feature extraction, neglecting abundant information from intermediate layers.
Bocheng Miao, Changbo Xu
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
Comparison of Topic Modelling Approaches in the Banking Context
Applied Sciences, 2023 Topic modelling is a prominent task for automatic topic extraction in many applications such as sentiment analysis and recommendation systems. The approach is vital for service industries to monitor their customer discussions.
Bayode Ogunleye +4 more
doaj +1 more source