Papers Document Classification
“Document Classification” 태그가 달린 논문 670편 · 필터 해제
Explainable and Discourse Topic-aware Neural Language Understanding
Marrying topic models and language models exposes language understanding to a broader source of document-level context beyond sentences via topics. While introducing topical semantics in language models, existing approac…
Document ClassificationLanguage ModelingLanguage ModellingRetrieval+4LSD-C: Linearly Separable Deep Clusters
We present LSD-C, a novel method to identify clusters in an unlabeled dataset. Our algorithm first establishes pairwise connections in the feature space between the samples of the minibatch based on a similarity metric. …
ClusteringData AugmentationDeep ClusteringDocument Classification+2Improving accuracy and speeding up Document Image Classification through parallel systems
This paper presents a study showing the benefits of the EfficientNet models compared with heavier Convolutional Neural Networks (CNNs) in the Document Classification task, essential problem in the digitalization process …
Document Classificationdocument-image-classificationDocument Image ClassificationGeneral Classification+5Document Classification for COVID-19 Literature
The global pandemic has made it more important than ever to quickly and accurately retrieve relevant scientific literature for effective consumption by researchers in a wide range of fields. We provide an analysis of sev…
ArticlesClassificationDocument ClassificationGeneral ClassificationWeb Document Categorization Using Naive Bayes Classifier and Latent Semantic Analysis
A rapid growth of web documents due to heavy use of World Wide Web necessitates efficient techniques to efficiently classify the document on the web. It is thus produced High volumes of data per second with high diversit…
ClassificationDocument Classificationfeature selectionGeneral ClassificationImprove Document Embedding for Text Categorization Through Deep Siamese Neural Network
Due to the increasing amount of data on the internet, finding a highly-informative, low-dimensional representation for text is one of the main challenges for efficient natural language processing tasks including text cla…
ClassificationDocument ClassificationDocument EmbeddingGeneral Classification+3Pre-training technique to localize medical BERT and enhance biomedical BERT
Pre-training large-scale neural language models on raw texts has made a significant contribution to improving transfer learning in natural language processing (NLP). With the introduction of transformer-based language mo…
Document ClassificationTransfer LearningPerformance evaluation of Machine learning algorithms in Biomedical Document Classification
Document classification is a prevalent task in Natural Language Processing (NLP) with a broad range of applications in the biomedical domain. In biomedical engineering categorization of biomedical literature into predefi…
BIG-bench Machine LearningClassificationDocument ClassificationNoise Pollution in Hospital Readmission Prediction: Long Document Classification with Reinforcement Learning
This paper presents a reinforcement learning approach to extract noise in long clinical documents for the task of readmission prediction after kidney transplant. We face the challenges of developing robust models on a sm…
Document ClassificationGeneral ClassificationReadmission Predictionreinforcement-learning+2Minimally Supervised Categorization of Text with Metadata
Document categorization, which aims to assign a topic label to each document, plays a fundamental role in a wide variety of applications. Despite the success of existing studies in conventional supervised document classi…
Document ClassificationTranslating Knowledge Representations with Monolingual Word Embeddings: the Case of a Thesaurus on Corporate Non-Financial Reporting
A common method of structuring information extracted from textual data is using a knowledge model (e.g. a thesaurus) to organise the information semantically. Creating and managing a knowledge model is already a costly t…
Cross-Lingual Word EmbeddingsDocument ClassificationWord EmbeddingsEmail Classification Incorporating Social Networks and Thread Structure
Existing methods for different document classification tasks in the context of social networks typically only capture the semantics of texts, while ignoring the users who exchange the text and the network they form. Howe…
ClassificationDocument ClassificationGeneral ClassificationSentiment AnalysisMassively Multilingual Sparse Word Representations
In this paper, we introduce Mamus for constructing multilingual sparse word representations. Our algorithm operates by determining a shared set of semantic units which get reutilized across languages, providing it a comp…
Dependency ParsingDocument ClassificationNatural Language InferenceSome people aren't worth listening to: periodically retraining classifiers with feedback from a team of end users
Document classification is ubiquitous in a business setting, but often the end users of a classifier are engaged in an ongoing feedback-retrain loop with the team that maintain it. We consider this feedback-retrain loop …
Document ClassificationCorpus-level and Concept-based Explanations for Interpretable Document Classification
Using attention weights to identify information that is important for models' decision-making is a popular approach to interpret attention-based neural networks. This is commonly realized in practice through the generati…
ClassificationDecision MakingDocument ClassificationGeneral ClassificationPrivacy at Scale: Introducing the PrivaSeer Corpus of Web Privacy Policies
Organisations disclose their privacy practices by posting privacy policies on their website. Even though users often care about their digital privacy, they often don't read privacy policies since they require a significa…
Document ClassificationKeyphrase ExtractionLight-Weighted CNN for Text Classification
For management, documents are categorized into a specific category, and to do these, most of the organizations use manual labor. In today's automation era, manual efforts on such a task are not justified, and to avoid th…
ClassificationDocument ClassificationDocument Image ClassificationDocument Text Classification+5SPECTER: Document-level Representation Learning using Citation-informed Transformers
Representation learning is a critical ingredient for natural language processing systems. Recent Transformer language models like BERT learn powerful textual representations, but these models are targeted towards token- …
Citation PredictionDocument ClassificationGeneral ClassificationLanguage Modeling+3Keyword Assisted Topic Models
In recent years, fully automated content analysis based on probabilistic topic models has become popular among social scientists because of their scalability. The unsupervised nature of the models makes them suitable for…
Document ClassificationTopic ModelsGender Detection on Social Networks using Ensemble Deep Learning
Analyzing the ever-increasing volume of posts on social media sites such as Facebook and Twitter requires improved information processing methods for profiling authorship. Document classification is central to this task,…
ClassificationDeep LearningDocument ClassificationGeneral Classification