A survey on text classification: From traditional to deep learning
Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …
processing. The last decade has seen a surge of research in this area due to the …
A survey on text classification: From shallow to deep learning
Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …
processing. The last decade has seen a surge of research in this area due to the …
Incorporating hierarchy into text encoder: a contrastive learning approach for hierarchical text classification
Hierarchical text classification is a challenging subtask of multi-label classification due to its
complex label hierarchy. Existing methods encode text and label hierarchy separately and …
complex label hierarchy. Existing methods encode text and label hierarchy separately and …
HPT: Hierarchy-aware prompt tuning for hierarchical text classification
Hierarchical text classification (HTC) is a challenging subtask of multi-label classification
due to its complex label hierarchy. Recently, the pretrained language models (PLM) have …
due to its complex label hierarchy. Recently, the pretrained language models (PLM) have …
SHO-CNN: A metaheuristic optimization of a convolutional neural network for multi-label news classification
News media always pursue informing the public at large. It is impossible to overestimate the
significance of understanding the semantics of news coverage. Traditionally, a news text is …
significance of understanding the semantics of news coverage. Traditionally, a news text is …
Exploiting global and local hierarchies for hierarchical text classification
Hierarchical text classification aims to leverage label hierarchy in multi-label text
classification. Existing methods encode label hierarchy in a global view, where label …
classification. Existing methods encode label hierarchy in a global view, where label …
Will AI solve the patent classification problem?
This paper scrutinizes the act of patent classification as it is performed by specialists, namely
patent examiners, and currently supported by automated systems in patent offices for …
patent examiners, and currently supported by automated systems in patent offices for …
[PDF][PDF] Hierarchical Text Classification: a review of current research
A Zangari, M Marcuzzo, M Schiavinato… - EXPERT SYSTEMS …, 2023 - iris.unive.it
It is often the case that collections of documents are annotated with hierarchically-structured
concepts. However, the benefits of this structure are rarely taken into account by …
concepts. However, the benefits of this structure are rarely taken into account by …
Improve label embedding quality through global sensitive GAT for hierarchical text classification
H Liu, X Huang, X Liu - Expert Systems with Applications, 2024 - Elsevier
Hierarchical text classification aims to assign text to multiple labels in a label set stored in a
tree structure. The current algorithms mainly introduce the priori information of the label …
tree structure. The current algorithms mainly introduce the priori information of the label …
Constrained sequence-to-tree generation for hierarchical text classification
Hierarchical Text Classification (HTC) is a challenging task where a document can be
assigned to multiple hierarchically structured categories within a taxonomy. The majority of …
assigned to multiple hierarchically structured categories within a taxonomy. The majority of …