Papers Document Classification
“Document Classification” 태그가 달린 논문 670편 · 필터 해제
Self-Discriminative Learning for Unsupervised Document Embedding
Unsupervised document representation learning is an important task providing pre-trained features for NLP applications. Unlike most previous work which learn the embedding based on self-prediction of the surface of text,…
Document ClassificationDocument EmbeddingGeneral ClassificationRepresentation LearningRethinking Complex Neural Network Architectures for Document Classification
Neural network models for many NLP tasks have grown increasingly complex in recent years, making training and deployment more difficult. A number of recent papers have questioned the necessity of such architectures and f…
ClassificationDocument ClassificationGeneral ClassificationLanguage Modeling+1A Semantic Cover Approach for Topic Modeling
We introduce a novel topic modeling approach based on constructing a semantic set cover for clusters of similar documents. Specifically, our approach first clusters documents using their Tf-Idf representation, and then c…
Document ClassificationGeneral ClassificationSemantic SimilaritySemantic Textual SimilarityNeural User Factor Adaptation for Text Classification: Learning to Generalize Across Author Demographics
Language use varies across different demographic factors, such as gender, age, and geographic location. However, most existing document classification methods ignore demographic variability. In this study, we examine emp…
ClassificationDocument ClassificationGeneral Classificationtext-classification+1Doris Martin at SemEval-2019 Task 4: Hyperpartisan News Detection with Generic Semi-supervised Features
In this paper we describe our participation to the Hyperpartisan News Detection shared task at SemEval 2019. Motivated by the late arrival of Doris Martin, we test a previously developed document classification system wh…
ClusteringDocument ClassificationGeneral ClassificationTeam Fernando-Pessa at SemEval-2019 Task 4: Back to Basics in Hyperpartisan News Detection
This paper describes our submission to the SemEval 2019 Hyperpartisan News Detection task. Our system aims for a linguistics-based document classification from a minimal set of interpretable features, while maintaining g…
Document ClassificationGeneral ClassificationMeta-LearningThe Pupil Has Become the Master: Teacher-Student Model-Based Word Embedding Distillation with Ensemble Learning
Recent advances in deep learning have facilitated the demand of neural models for real applications. In practice, these applications often need to be deployed with limited resources while keeping high accuracy. This pape…
Document ClassificationEnsemble LearningSentiment AnalysisWord EmbeddingsFAN: Focused Attention Networks
Attention networks show promise for both vision and language tasks, by emphasizing relationships between constituent elements through weighting functions. Such elements could be regions in an image output by a region pro…
Document ClassificationObject DetectionRegion ProposalSentenceObject detection deep learning networks for Optical Character Recognition
In this article, we show how we applied a simple approach coming from deep learning networks for object detection to the task of optical character recognition in order to build image features taylored for documents. In c…
Deep LearningDocument ClassificationGeneral ClassificationObject+4Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT
Pretrained contextual representation models (Peters et al., 2018; Devlin et al., 2018) have pushed forward the state-of-the-art on many NLP tasks. A new release of BERT (Devlin, 2018) includes a model simultaneously pret…
Cross-Lingual NERCross-Lingual TransferDependency ParsingDocument Classification+5DocBERT: BERT for Document Classification
We present, to our knowledge, the first application of BERT to document classification. A few characteristics of the task might lead one to think that BERT is not the most appropriate model: syntactic structures matter l…
ClassificationDocument ClassificationGeneral ClassificationSentiment Analysis+1Adaptively Connected Neural Networks
This paper presents a novel adaptively connected neural network (ACNet) to improve the traditional convolutional neural networks (CNNs) {in} two aspects. First, ACNet employs a flexible way to switch global and local inf…
Document ClassificationImage ClassificationPerson Re-IdentificationExplainable Text Classification in Legal Document Review A Case Study of Explainable Predictive Coding
In today's legal environment, lawsuits and regulatory investigations require companies to embark upon increasingly intensive data-focused engagements to identify, collect and analyze large quantities of data. When docume…
Document ClassificationGeneral Classificationtext-classificationText ClassificationCo-regularized Multi-view Sparse Reconstruction Embedding for Dimension Reduction
With the development of information technology, we have witnessed an age of data explosion which produces a large variety of data filled with redundant information. Because dimension reduction is an essential tool which …
Dimensionality ReductionDocument ClassificationFace RecognitionImage Retrieval+1Interpretable Structure-aware Document Encoders with Hierarchical Attention
We propose a method to create document representations that reflect their internal structure. We modify Tree-LSTMs to hierarchically merge basic elements such as words and sentences into blocks of increasing complexity. …
Document ClassificationSentenceWord EmbeddingsLeveraging Deep Graph-Based Text Representation for Sentiment Polarity Applications
Over the last few years, machine learning over graph structures has manifested a significant enhancement in text mining applications such as event detection, opinion mining, and news recommendation. One of the primary ch…
BIG-bench Machine LearningDocument ClassificationEvent DetectionInformation Retrieval+7Glyce: Glyph-vectors for Chinese Character Representations
It is intuitive that NLP tasks for logographic languages like Chinese should benefit from the use of the glyph information in those languages. However, due to the lack of rich pictographic evidence in glyphs and the weak…
Chinese Dependency ParsingChinese Named Entity RecognitionChinese Part-of-Speech TaggingChinese Semantic Role Labeling+22Hierarchical Attentional Hybrid Neural Networks for Document Classification
Document classification is a challenging task with important applications. The deep learning approaches to the problem have gained much attention recently. Despite the progress, the proposed models do not incorporate the…
ClassificationDocument ClassificationGeneral ClassificationText ClassificationMassively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
We introduce an architecture to learn joint multilingual sentence representations for 93 languages, belonging to more than 30 different families and written in 28 different scripts. Our system uses a single BiLSTM encode…
Cross-Lingual Bitext MiningCross-Lingual Document ClassificationCross-Lingual Natural Language InferenceCross-Lingual Transfer+8Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification
Text classification must sometimes be applied in a low-resource language with no labeled training data. However, training data may be available in a related language. We investigate whether character-level knowledge tran…
ClassificationCross-Lingual Document ClassificationDocument ClassificationGeneral Classification+3