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A Weighted Diffusion Graph Convolutional Network for Relation Extraction
Journal of Electrical and Computer Engineering, Volume 2024, Issue 1, 2024.Currently, graph convolutional network (GCN) is widely used in relation extraction (RE) tasks. Within RE tasks in the form of directed graphs, the placement of entities in the sentence context generates a large number of remote entity nodes in the directed graph.
Jiusheng Chen +4 more
wiley +1 more source
Relation Classification via Recurrent Neural Network with Attention and Tensor Layers
Big Data Mining and Analytics, 2018 Relation classification is a crucial component in many Natural Language Processing (NLP) systems. In this paper, we propose a novel bidirectional recurrent neural network architecture (using Long Short-Term Memory, LSTM, cells) for relation ...
Runyan Zhang +3 more
doaj +1 more source
A Hybrid Deep Implicit Neural Model for Sentiment Analysis via Transfer Learning
IEEE AccessWe present a neural model for sentiment analysis of social network texts with a special focus on cryptocurrency-related content using deep transfer learning. A challenge of deep learning is its need for abundant data.
Kia Jahanbin, Mohammad Ali Zare Chahooki
doaj +1 more source
Breaking Sticks and Ambiguities with Adaptive Skip-gram
, 2015 Recently proposed Skip-gram model is a powerful method for learning high-dimensional word representations that capture rich semantic relationships between words. However, Skip-gram as well as most prior work on learning word representations does not take
Bartunov, Sergey +3 more
core +1 more source
Explainable Aspect-Based Sentiment Analysis Using Transformer Models
Big Data and Cognitive ComputingAn aspect-based sentiment analysis (ABSA) aims to perform a fine-grained analysis of text to identify sentiments and opinions associated with specific aspects.
Isidoros Perikos +1 more
doaj +1 more source
Identifying interactions between chemical entities in biomedical text
Journal of Integrative Bioinformatics, 2014 Interactions between chemical compounds described in biomedical text can be of great importance to drug discovery and design, as well as pharmacovigilance.
Lamurias Andre +2 more
doaj +1 more source