A Systematic Review of Cross-Lingual Sentiment Analysis: Tasks, Strategies, and Prospects
C Zhao, M Wu, X Yang, W Zhang, S Zhang… - ACM Computing …, 2024 - dl.acm.org
Traditional methods for sentiment analysis, when applied in a monolingual context, often
yield less than optimal results in multilingual settings. This underscores the need for a more …
yield less than optimal results in multilingual settings. This underscores the need for a more …
Multiplex graph neural network for extractive text summarization
Extractive text summarization aims at extracting the most representative sentences from a
given document as its summary. To extract a good summary from a long text document …
given document as its summary. To extract a good summary from a long text document …
Soft Hybrid Knowledge Distillation against deep neural networks
Traditional knowledge distillation approaches are typically designed for specific tasks, as
they primarily distilling deep features from intermediate layers of a neural network, generally …
they primarily distilling deep features from intermediate layers of a neural network, generally …
Semi-supervised learning models for document classification: A systematic review and meta-analysis
A Cevallos-Culqui, C Pons, G Rodriguez - Inteligencia Artificial, 2023 - journal.iberamia.org
The continuous increase of digital documents on the web creates the need to search for
information patterns that allow the categorization of organizational documents to generate …
information patterns that allow the categorization of organizational documents to generate …
KDPG-Enhanced MRC Framework for Scientific Entity Recognition in Survey Papers
M Hu, L Qian, Z Chang, Z Zhang - IEEE/ACM Transactions on …, 2024 - ieeexplore.ieee.org
Scientific survey papers play a pivotal role in advancing knowledge and scientific progress
by providing concise summaries and analyses of research trends and findings. To facilitate …
by providing concise summaries and analyses of research trends and findings. To facilitate …
Heterogeneous Contrastive Learning for Foundation Models and Beyond
In the era of big data and Artificial Intelligence, an emerging paradigm is to utilize contrastive
self-supervised learning to model large-scale heterogeneous data. Many existing foundation …
self-supervised learning to model large-scale heterogeneous data. Many existing foundation …
Transductive Transfer Dictionary Learning Algorithm for Remote Sensing Image Classification.
J Zhu, H Chen, Y Fan, T Ni - CMES-Computer Modeling in …, 2023 - search.ebscohost.com
To create a green and healthy living environment, people have put forward higher
requirements for the refined management of ecological resources. A variety of technologies …
requirements for the refined management of ecological resources. A variety of technologies …
Clustering-Enhanced Knowledge Graph Embedding
Abstract Knowledge graph embedding (KGE) is a task to transform the symbolic entities and
relations in Knowledge Graphs (KGs) into low-dimensional vectors, which facilitates the use …
relations in Knowledge Graphs (KGs) into low-dimensional vectors, which facilitates the use …
Clustering-Enhanced Knowledge Graph Embedding
J Gu, Z Shi - Big Data: 10th CCF Conference, BigData 2022 …, 2022 - books.google.com
Knowledge graph embedding (KGE) is a task to transform the symbolic entities and relations
in Knowledge Graphs (KGs) into lowdimensional vectors, which facilitates the use of KGs in …
in Knowledge Graphs (KGs) into lowdimensional vectors, which facilitates the use of KGs in …
[PDF][PDF] Cross-Cultural Deep Learning Models for Sentiment Analysis Between Chinese and Japanese Using Sentiment Features
F Su, J Liu, Y Hao - 2024 - cad-journal.net
With pre-trained bilingual word embedding (BWE) dictionaries, deep learning-based cross-
language sentiment analysis models require text vector representations in both the source …
language sentiment analysis models require text vector representations in both the source …