Papers Document Classification
“Document Classification” 태그가 달린 논문 670편 · 필터 해제
TopicBERT for Energy Efficient Document Classification
Prior research notes that BERT's computational cost grows quadratically with sequence length thus leading to longer training times, higher GPU memory constraints and carbon emissions. While recent work seeks to address t…
ClassificationDocument ClassificationGeneral ClassificationGPUText Classification Using Label Names Only: A Language Model Self-Training Approach
Current text classification methods typically require a good number of human-labeled documents as training data, which can be costly and difficult to obtain in real applications. Humans can perform classification without…
ClassificationDocument ClassificationGeneral ClassificationLanguage Modeling+7Aspect-based Document Similarity for Research Papers
Traditional document similarity measures provide a coarse-grained distinction between similar and dissimilar documents. Typically, they do not consider in what aspects two documents are similar. This limits the granulari…
Document ClassificationRecommendation SystemsLegal Document Classification: An Application to Law Area Prediction of Petitions to Public Prosecution Service
In recent years, there has been an increased interest in the application of Natural Language Processing (NLP) to legal documents. The use of convolutional and recurrent neural networks along with word embedding technique…
ClassificationDocument ClassificationGeneral ClassificationSentiment Analysis+1Causal Feature Selection with Dimension Reduction for Interpretable Text Classification
Text features that are correlated with class labels, but do not directly cause them, are sometimesuseful for prediction, but they may not be insightful. As an alternative to traditional correlation-basedfeature selection…
Causal InferenceClassificationDimensionality ReductionDocument Classification+4Neural RST-based Evaluation of Discourse Coherence
This paper evaluates the utility of Rhetorical Structure Theory (RST) trees and relations in discourse coherence evaluation. We show that incorporating silver-standard RST features can increase accuracy when classifying …
Coherence EvaluationDiscourse ParsingDocument ClassificationNatural Language Understanding+1Towards a Multi-modal, Multi-task Learning based Pre-training Framework for Document Representation Learning
Recent approaches in literature have exploited the multi-modal information in documents (text, layout, image) to serve specific downstream document tasks. However, they are limited by their - (i) inability to learn cross…
Document ClassificationMulti-Task LearningRepresentation LearningRetrievalImmigration Document Classification and Automated Response Generation
In this paper, we consider the problem of organizing supporting documents vital to U.S. work visa petitions, as well as responding to Requests For Evidence (RFE) issued by the U.S.~Citizenship and Immigration Services (U…
ClassificationDocument ClassificationGeneral ClassificationResponse GenerationCascaded Semantic and Positional Self-Attention Network for Document Classification
Transformers have shown great success in learning representations for language modelling. However, an open challenge still remains on how to systematically aggregate semantic information (word embedding) with positional …
ClassificationDocument ClassificationGeneral ClassificationLanguage ModellingData Programming by Demonstration: A Framework for Interactively Learning Labeling Functions
Data programming is a programmatic weak supervision approach to efficiently curate large-scale labeled training data. Writing data programs (labeling functions) requires, however, both programming literacy and domain exp…
Document ClassificationLabel-Wise Document Pre-Training for Multi-Label Text Classification
A major challenge of multi-label text classification (MLTC) is to stimulatingly exploit possible label differences and label correlations. In this paper, we tackle this challenge by developing Label-Wise Pre-Training (LW…
ClassificationDocument ClassificationGeneral ClassificationMulti Label Text Classification+3Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing
Pretraining large neural language models, such as BERT, has led to impressive gains on many natural language processing (NLP) tasks. However, most pretraining efforts focus on general domain corpora, such as newswire and…
Continual PretrainingDocument ClassificationDrug–drug Interaction Extraction+12A Study of fastText Word Embedding Effects in Document Classification in Bangla Language
Natural language processing is the current topic due to many important tasks like document classification, named entity recognition, opinion mining, sentiment analysis, textual entailment, etc. Such types of task in the …
ClassificationDocument ClassificationGeneral ClassificationLemmatization+6XD at SemEval-2020 Task 12: Ensemble Approach to Offensive Language Identification in Social Media Using Transformer Encoders
This paper presents six document classification models using the latest transformer encoders and a high-performing ensemble model for a task of offensive language identification in social media. For the individual models…
DecoderDocument ClassificationLanguage IdentificationEvaluation of Neural Network Classification Systems on Document Stream
One major drawback of state of the art Neural Networks (NN)-based approaches for document classification purposes is the large number of training samples required to obtain an efficient classification. The minimum requir…
ClassificationDocument ClassificationGeneral ClassificationDomain Adaptation and Instance Selection for Disease Syndrome Classification over Veterinary Clinical Notes
Identifying the reasons for antibiotic administration in veterinary records is a critical component of understanding antimicrobial usage patterns. This informs antimicrobial stewardship programs designed to fight antimic…
Document ClassificationDomain AdaptationGeneral ClassificationExploring the Limits of Simple Learners in Knowledge Distillation for Document Classification with DocBERT
Fine-tuned variants of BERT are able to achieve state-of-the-art accuracy on many natural language processing tasks, although at significant computational costs. In this paper, we verify BERT{'}s effectiveness for docume…
Document ClassificationGeneral ClassificationKnowledge DistillationModel CompressionA Confidence-Calibrated MOBA Game Winner Predictor
In this paper, we propose a confidence-calibration method for predicting the winner of a famous multiplayer online battle arena (MOBA) game, League of Legends. In MOBA games, the dataset may contain a large amount of inp…
Document ClassificationBiologically Plausible Learning of Text Representation with Spiking Neural Networks
This study proposes a novel biologically plausible mechanism for generating low-dimensional spike-based text representation. First, we demonstrate how to transform documents into series of spikes spike trains which are s…
Document ClassificationGeneral Classificationtext-classificationText ClassificationAraDIC: Arabic Document Classification using Image-Based Character Embeddings and Class-Balanced Loss
Classical and some deep learning techniques for Arabic text classification often depend on complex morphological analysis, word segmentation, and hand-crafted feature engineering. These could be eliminated by using chara…
ClassificationDeep LearningDocument ClassificationFeature Engineering+4