Papers Multi-Label Text Classification
“Multi-Label Text Classification” 태그가 달린 논문 181편 · 필터 해제
Pairwise Instance Relation Augmentation for Long-tailed Multi-label Text Classification
Multi-label text classification (MLTC) is one of the key tasks in natural language processing. It aims to assign multiple target labels to one document. Due to the uneven popularity of labels, the number of documents per…
DiversityMulti Label Text ClassificationMulti-Label Text ClassificationRelation+2Hierarchical Multi-Label Classification of Scientific Documents
Automatic topic classification has been studied extensively to assist managing and indexing scientific documents in a digital collection. With the large number of topics being available in recent years, it has become nec…
ClassificationHierarchical Multi-label ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+4Enhancing Chinese Multi-Label Text Classification Performance with Response-based Knowledge Distillation
It’s difficult to optimize individual label performance of multi-label text classification, especially in those imbalanced data containing long-tailed labels. Therefore, this study proposes a response-based knowledge dis…
Knowledge DistillationMulti Label Text ClassificationMulti-Label Text Classificationtext-classification+1CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label Classification
Extreme Multi-label Text Classification (XMC) involves learning a classifier that can assign an input with a subset of most relevant labels from millions of label choices. Recent approaches, such as XR-Transformer and Li…
Extreme Multi-Label ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATIONMulti Label Text Classification+3BERT-Flow-VAE: A Weakly-supervised Model for Multi-Label Text Classification
Multi-label Text Classification (MLTC) is the task of categorizing documents into one or more topics. Considering the large volumes of data and varying domains of such tasks, fully supervised learning requires manually f…
Multi Label Text ClassificationMulti-Label Text ClassificationNatural Language InferenceSentence+3OTSeq2Set: An Optimal Transport Enhanced Sequence-to-Set Model for Extreme Multi-label Text Classification
Extreme multi-label text classification (XMTC) is the task of finding the most relevant subset labels from an extremely large-scale label collection. Recently, some deep learning models have achieved state-of-the-art res…
Multi Label Text ClassificationMulti-Label Text Classificationtext-classificationText Classification生成模型在层次结构极限多标签文本分类中的应用(Generation Model for Hierarchical Extreme Multi-label Text Classification)
“层次结构极限多标签文本分类是自然语言处理研究领域中一个重要而又具有挑战性的课题。该任务类别标签数量巨大且自成体系,标签与标签之间还具有不同层级间的依赖关系或同层次间的相关性,这些特性进一步增加了任务难度。该文提出将层次结构极限多标签文本分类任务视为序列转换问题,将输出标签视为序列,从而可以直接从数十万标签中生成与文本相关的类别标签。通过软约束机制和词表复合映射在解码过程中利用标签之间的层次结构与相关信息。实验结果表明,该文提出的方法与…
Multi Label Text ClassificationMulti-Label Text Classificationtext-classificationText ClassificationA Multi-Dimensional, Cross-Domain and Hierarchy-Aware Neural Architecture for ISO-Standard Dialogue Act Tagging
Dialogue Act tagging with the ISO 24617-2 standard is a difficult task that involves multi-label text classification across a diverse set of labels covering semantic, syntactic and pragmatic aspects of dialogue. The lack…
Multi Label Text ClassificationMulti-Label Text Classificationtext-classificationText ClassificationCorrelation Networks for Extreme Multi-label Text Classification
This paper develops the Correlation Networks (CorNet) architecture for the extreme multi-label text classification (XMTC) task, where the objective is to tag an input text sequence with the most relevant subset of labels…
ClassificationMulti Label Text ClassificationMulti-Label Text ClassificationTAG+2SSN_NLP_MLRG at SemEval-2022 Task 4: Ensemble Learning strategies to detect Patronizing and Condescending Language
In this paper, we describe our efforts at SemEval 2022 Shared Task 4 on Patronizing and Condescending Language (PCL) Detection. This is the first shared task to detect PCL which is to identify and categorize PCL language…
ClassificationEnsemble LearningMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+4HITMI&T at SemEval-2022 Task 4: Investigating Task-Adaptive Pretraining And Attention Mechanism On PCL Detection
This paper describes the system for the Semeval-2022 Task4 ”Patronizing and Condescending Language Detection”.An entity engages in Patronizing and Condescending Language(PCL) when its language use shows a superior attitu…
Multi Label Text ClassificationMulti-Label Text ClassificationSentencetext-classification+1Even the Simplest Baseline Needs Careful Re-investigation: A Case Study on XML-CNN
The power and the potential of deep learning models attract many researchers to design advanced and sophisticated architectures. Nevertheless, the progress is sometimes unreal due to various possible reasons. In this wor…
Deep LearningMulti Label Text ClassificationMulti-Label Text Classificationtext-classification+1Investigating Active Learning Sampling Strategies for Extreme Multi Label Text Classification
Large scale, multi-label text datasets with high numbers of different classes are expensive to annotate, even more so if they deal with domain specific language. In this work, we aim to build classifiers on these dataset…
Active LearningExtreme Multi-Label ClassificationMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+4Exploiting Dynamic and Fine-grained Semantic Scope for Extreme Multi-label Text Classification
Extreme multi-label text classification (XMTC) refers to the problem of tagging a given text with the most relevant subset of labels from a large label set. A majority of labels only have a few training instances due to …
Multi Label Text ClassificationMulti-Label Text Classificationtext-classificationText ClassificationRaFoLa: A Rationale-Annotated Corpus for Detecting Indicators of Forced Labour
Forced labour is the most common type of modern slavery, and it is increasingly gaining the attention of the research and social community. Recent studies suggest that artificial intelligence (AI) holds immense potential…
ArticlesMulti Label Text ClassificationMulti-Label Text Classificationtext-classification+1Exploiting 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 hierarchy is treated as the static hierarchical …
ClassificationMulti Label Text ClassificationMulti-Label Text Classificationtext-classification+1Contrastive Learning-Enhanced Nearest Neighbor Mechanism for Multi-Label Text Classification
Multi-Label Text Classification (MLTC) is a fundamental and challenging task in natural language processing. Previous studies mainly focus on learning text representation and modeling label correlation but neglect the ri…
Contrastive LearningMulti Label Text ClassificationMulti-Label Text Classificationtext-classification+1HFT-ONLSTM: Hierarchical and Fine-Tuning Multi-label Text Classification
Many important classification problems in the real-world consist of a large number of closely related categories in a hierarchical structure or taxonomy. Hierarchical multi-label text classification (HMTC) with higher ac…
ClassificationMulti Label Text ClassificationMulti-Label Text Classificationtext-classification+1An Ensemble Learning Based Approach to Multi-label Power Text Classification for Fault-type Recognition
With the rapid development of ICT Custom Services (ICT CS) in power industries, the deployed power ICT CS systems mainly rely on the experience of customer service staff for fault type recognition, questioning, and answe…
ClassificationEnsemble LearningMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+5Are We Really Making Much Progress in Text Classification? A Comparative Review
We analyze various methods for single-label and multi-label text classification across well-known datasets, categorizing them into bag-of-words, sequence-based, graph-based, and hierarchical approaches. Despite the surge…
ClassificationDecoderMulti-Label ClassificationMulti Label Text Classification+3