A comprehensive survey on deep graph representation learning
Graph representation learning aims to effectively encode high-dimensional sparse graph-
structured data into low-dimensional dense vectors, which is a fundamental task that has …
structured data into low-dimensional dense vectors, which is a fundamental task that has …
Fake news detection: A survey of graph neural network methods
The emergence of various social networks has generated vast volumes of data. Efficient
methods for capturing, distinguishing, and filtering real and fake news are becoming …
methods for capturing, distinguishing, and filtering real and fake news are becoming …
Dependency-driven relation extraction with attentive graph convolutional networks
Syntactic information, especially dependency trees, has been widely used by existing
studies to improve relation extraction with better semantic guidance for analyzing the context …
studies to improve relation extraction with better semantic guidance for analyzing the context …
Cross-modal multitask transformer for end-to-end multimodal aspect-based sentiment analysis
As an emerging task in opinion mining, End-to-End Multimodal Aspect-Based Sentiment
Analysis (MABSA) aims to extract all the aspect-sentiment pairs mentioned in a pair of …
Analysis (MABSA) aims to extract all the aspect-sentiment pairs mentioned in a pair of …
Joint multi-modal aspect-sentiment analysis with auxiliary cross-modal relation detection
Aspect terms extraction (ATE) and aspect sentiment classification (ASC) are two
fundamental and fine-grained sub-tasks in aspect-level sentiment analysis (ALSA). In the …
fundamental and fine-grained sub-tasks in aspect-level sentiment analysis (ALSA). In the …
Vision-language pre-training for multimodal aspect-based sentiment analysis
As an important task in sentiment analysis, Multimodal Aspect-Based Sentiment Analysis
(MABSA) has attracted increasing attention in recent years. However, previous approaches …
(MABSA) has attracted increasing attention in recent years. However, previous approaches …
A semantic and syntactic enhanced neural model for financial sentiment analysis
This paper studies the methodology of inferring bullish or bearish sentiments in the financial
domain. The task aims to predict a real value to represent the sentiment intensity concerning …
domain. The task aims to predict a real value to represent the sentiment intensity concerning …
Sentiment interaction and multi-graph perception with graph convolutional networks for aspect-based sentiment analysis
Q Lu, X Sun, R Sutcliffe, Y Xing, H Zhang - Knowledge-Based Systems, 2022 - Elsevier
Graph convolutional networks have been successfully applied to aspect-based sentiment
analysis, due to their ability to flexibly capture syntactic information and word dependencies …
analysis, due to their ability to flexibly capture syntactic information and word dependencies …
A Lexicon Enhanced Collaborative Network for targeted financial sentiment analysis
L Shang, H Xi, J Hua, H Tang, J Zhou - Information Processing & …, 2023 - Elsevier
The increasing interest around emotions in online texts creates the demand for financial
sentiment analysis. Previous studies mainly focus on coarse-grained document-/sentence …
sentiment analysis. Previous studies mainly focus on coarse-grained document-/sentence …
RevCore: Review-augmented conversational recommendation
Existing conversational recommendation (CR) systems usually suffer from insufficient item
information when conducted on short dialogue history and unfamiliar items. Incorporating …
information when conducted on short dialogue history and unfamiliar items. Incorporating …