Papers Document Classification
“Document Classification” 태그가 달린 논문 670편 · 필터 해제
Balancing Methods for Multi-label Text Classification with Long-Tailed Class Distribution
Multi-label text classification is a challenging task because it requires capturing label dependencies. It becomes even more challenging when class distribution is long-tailed. Resampling and re-weighting are common appr…
Document ClassificationMulti-Label Text ClassificationText ClassificationMultiEURLEX -- A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer
We introduce MULTI-EURLEX, a new multilingual dataset for topic classification of legal documents. The dataset comprises 65k European Union (EU) laws, officially translated in 23 languages, annotated with multiple labels…
Cross-Lingual TransferDocument ClassificationTopic ClassificationZero-Shot Cross-Lingual TransferTowards Explaining STEM Document Classification using Mathematical Entity Linking
Document subject classification is essential for structuring (digital) libraries and allowing readers to search within a specific field. Currently, the classification is typically made by human domain experts. Semi-super…
ClassificationDocument ClassificationEntity LinkingDomain-Specific Japanese ELECTRA Model Using a Small Corpus
Recently, domain shift, which affects accuracy due to differences in data between source and target domains, has become a serious issue when using machine learning methods to solve natural language processing tasks. With…
ArticlesComputational EfficiencyDocument ClassificationLanguage Modeling+2Application of Mix-Up Method in Document Classification Task Using BERT
The mix-up method (Zhang et al., 2017), one of the methods for data augmentation, is known to be easy to implement and highly effective. Although the mix-up method is intended for image identification, it can also be app…
ClassificationData AugmentationDocument ClassificationSentenceImproving Neural Language Processing with Named Entities
Pretraining-based neural network models have demonstrated state-of-the-art (SOTA) performances on natural language processing (NLP) tasks. The most frequently used sentence representation for neural-based NLP methods is …
Document ClassificationHeadline GenerationPart-Of-Speech TaggingPOS+2Exploring Out-of-Distribution Generalization in Text Classifiers Trained on Tobacco-3482 and RVL-CDIP
To be robust enough for widespread adoption, document analysis systems involving machine learning models must be able to respond correctly to inputs that fall outside of the data distribution that was used to generate th…
Document ClassificationOut-of-Distribution Generalizationtext-classificationText ClassificationPyEuroVoc: A Tool for Multilingual Legal Document Classification with EuroVoc Descriptors
EuroVoc is a multilingual thesaurus that was built for organizing the legislative documentary of the European Union institutions. It contains thousands of categories at different levels of specificity and its descriptors…
Document ClassificationSpecificityModeling Text using the Continuous Space Topic Model with Pre-Trained Word Embeddings
In this study, we propose a model that extends the continuous space topic model (CSTM), which flexibly controls word probability in a document, using pre-trained word embeddings. To develop the proposed model, we pre-tra…
Document ClassificationWord EmbeddingsMultilingual Protest News Detection - Shared Task 1, CASE 2021
Benchmarking state-of-the-art text classification and information extraction systems in multilingual, cross-lingual, few-shot, and zero-shot settings for socio-political event information collection is achieved in the sc…
BenchmarkingDecision MakingDocument ClassificationEvent Extraction+5DYPLODOC: Dynamic Plots for Document Classification
Narrative generation and analysis are still on the fringe of modern natural language processing yet are crucial in a variety of applications. This paper proposes a feature extraction method for plot dynamics. We present …
ClassificationDocument ClassificationA comparison of latent semantic analysis and correspondence analysis of document-term matrices
Latent semantic analysis (LSA) and correspondence analysis (CA) are two techniques that use a singular value decomposition (SVD) for dimensionality reduction. LSA has been extensively used to obtain low-dimensional repre…
Authorship AttributionDimensionality ReductionDocument ClassificationText CategorizationBenchmarking for Biomedical Natural Language Processing Tasks with a Domain Specific ALBERT
The availability of biomedical text data and advances in natural language processing (NLP) have made new applications in biomedical NLP possible. Language models trained or fine tuned using domain specific corpora can ou…
BenchmarkingDocument Classificationnamed-entity-recognitionNamed Entity Recognition+5Bengali text document categorization based on very deep convolution neural network
In recent years, the amount of digital text contents or documents in the Bengali language has increased enormously on online platforms due to the effortless access of the Internet via electronic gadgets. As a result, an …
ClassificationDocument Classificationtext-classificationText ClassificationDeep Learning for Technical Document Classification
In large technology companies, the requirements for managing and organizing technical documents created by engineers and managers have increased dramatically in recent years, which has led to a higher demand for more sca…
ClassificationDecision MakingDeep LearningDescriptive+6Efficient Document Image Classification Using Region-Based Graph Neural Network
Document image classification remains a popular research area because it can be commercialized in many enterprise applications across different industries. Recent advancements in large pre-trained computer vision and lan…
ClassificationDocument Classificationdocument-image-classificationDocument Image Classification+3TagRuler: Interactive Tool for Span-Level Data Programming by Demonstration
Despite rapid developments in the field of machine learning research, collecting high-quality labels for supervised learning remains a bottleneck for many applications. This difficulty is exacerbated by the fact that sta…
Active LearningDocument ClassificationAn Automated Knowledge Mining and Document Classification System with Multi-model Transfer Learning
Service manual documents are crucial to the engineering company as they provide guidelines and knowledge to service engineers. However, it has become inconvenient and inefficient for service engineers to retrieve specifi…
CoLADocument ClassificationLinguistic AcceptabilityTransfer LearningA Sentence-level Hierarchical BERT Model for Document Classification with Limited Labelled Data
Training deep learning models with limited labelled data is an attractive scenario for many NLP tasks, including document classification. While with the recent emergence of BERT, deep learning language models can achieve…
ClassificationDocument ClassificationSentenceAn Intelligent Hybrid Model for Identity Document Classification
Digitization, i.e., the process of converting information into a digital format, may provide various opportunities (e.g., increase in productivity, disaster recovery, and environmentally friendly solutions) and challenge…
ClassificationDocument Classificationimage-classificationImage Classification+1