4.6 Article

Commonsense knowledge graph-based adapter for aspect-level sentiment classification

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

Aspect-based sentiment analysis via affective knowledge enhanced graph convolutional networks

Bin Liang et al.

Summary: This paper proposes a graph convolutional network model Sentic GCN based on SenticNet to enhance the affective dependencies of sentences for aspect-based sentiment analysis. By integrating emotional knowledge from SenticNet, the model effectively handles contextual affective information in sentences, improving the effectiveness of sentiment polarity detection towards specific aspects.

KNOWLEDGE-BASED SYSTEMS (2022)

Article Computer Science, Artificial Intelligence

SK-GCN: Modeling Syntax and Knowledge via Graph Convolutional Network for aspect-level sentiment classification

Jie Zhou et al.

KNOWLEDGE-BASED SYSTEMS (2020)

Article Computer Science, Artificial Intelligence

Knowledge Graph Embedding: A Survey of Approaches and Applications

Quan Wang et al.

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2017)

Proceedings Paper Computer Science, Interdisciplinary Applications

Attention-over-Attention Neural Networks for Reading Comprehension

Yiming Cui et al.

PROCEEDINGS OF THE 55TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2017), VOL 1 (2017)

Proceedings Paper Computer Science, Artificial Intelligence

Fast and Space-Efficient Entity Linking in Queries

Roi Blanco et al.

WSDM'15: PROCEEDINGS OF THE EIGHTH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING (2015)

Proceedings Paper Computer Science, Information Systems

DBpedia: A nucleus for a web of open data

Soeren Auer et al.

SEMANTIC WEB, PROCEEDINGS (2007)