Oct 12, 2024 · This work aims to summarize and categorize various GCN-based Text Classification approaches with regard to the architecture and mode of supervision.

1 day ago · This approach to graph representation learning is applicable to fields such as text mining and information retrieval, offering a rich set of features for ...

Jul 12, 2024 · This article explores the fundamental concepts, various algorithms, and applications of graph-based ranking in text mining.

Jul 1, 2024 · In this survey, we bring the coverage of methods up to 2023, including corpus-level and document-level graph neural networks.

Aug 15, 2024 · This paper proposes a novel graph classification method based on the subgraph-level feature the high-difference-frequency subgraph.

Jun 5, 2024 · This paper proposes a deep learning-driven framework designed to enhance the effectiveness of text classification models.

Aug 23, 2024 · Text classification using hypergraph algorithms is effective in capturing the intricate relationships between words and phrases in documents. The method entails ...

Jul 5, 2024 · In this survey, we bring the coverage of methods up to 2023, including corpus-level and document-level graph neural networks.

Aug 25, 2024 · This paper aims to conduct a comprehensive evaluation of modern text classification algorithms through empirical and experimental assessments.

Jan 31, 2024 · It involves the use of natural language processing (NLP) techniques to extract useful information and insights from large amounts of unstructured text data.