Papers Document Classification
“Document Classification” 태그가 달린 논문 670편 · 필터 해제
Classification Benchmarks for Under-resourced Bengali Language based on Multichannel Convolutional-LSTM Network
Exponential growths of social media and micro-blogging sites not only provide platforms for empowering freedom of expressions and individual voices but also enables people to express anti-social behaviour like online har…
ArticlesClassificationDocument ClassificationGeneral Classification+3A Simple Approach to Learning Unsupervised Multilingual Embeddings
Recent progress on unsupervised learning of cross-lingual embeddings in bilingual setting has given impetus to learning a shared embedding space for several languages without any supervision. A popular framework to solve…
Bilingual Lexicon InductionDependency ParsingDocument ClassificationWord Alignment+1Pruning and Sparsemax Methods for Hierarchical Attention Networks
This paper introduces and evaluates two novel Hierarchical Attention Network models [Yang et al., 2016] - i) Hierarchical Pruned Attention Networks, which remove the irrelevant words and sentences from the classification…
Document ClassificationGeneral ClassificationSentiment AnalysisSource Printer Identification from Document Images Acquired using Smartphone
Vast volumes of printed documents continue to be used for various important as well as trivial applications. Such applications often rely on the information provided in the form of printed text documents whose integrity …
Document ClassificationGeneral ClassificationPairwise Multi-Class Document Classification for Semantic Relations between Wikipedia Articles
Many digital libraries recommend literature to their users considering the similarity between a query document and their repository. However, they often fail to distinguish what is the relationship that makes two documen…
ArticlesDocument ClassificationGeneral ClassificationRecommendation SystemsText classification with word embedding regularization and soft similarity measure
Since the seminal work of Mikolov et al., word embeddings have become the preferred word representations for many natural language processing tasks. Document similarity measures extracted from word embeddings, such as th…
ClassificationDocument ClassificationGeneral Classificationtext-classification+4Sets Clustering
The input to the \emph{sets-$k$-means} problem is an integer $k\geq 1$ and a set $\mathcal{P}=\{P_1,\cdots,P_n\}$ of sets in $\mathbb{R}^d$. The goal is to compute a set $C$ of $k$ centers (points) in $\mathbb{R}^d$ that…
ClusteringDocument ClassificationCross-GCN: Enhancing Graph Convolutional Network with $k$-Order Feature Interactions
Graph Convolutional Network (GCN) is an emerging technique that performs learning and reasoning on graph data. It operates feature learning on the graph structure, through aggregating the features of the neighbor nodes t…
Document ClassificationContrastive estimation reveals topic posterior information to linear models
Contrastive learning is an approach to representation learning that utilizes naturally occurring similar and dissimilar pairs of data points to find useful embeddings of data. In the context of document classification un…
ClassificationContrastive LearningDocument ClassificationGeneral Classification+1Benchmark Performance of Machine And Deep Learning Based Methodologies for Urdu Text Document Classification
In order to provide benchmark performance for Urdu text document classification, the contribution of this paper is manifold. First, it pro-vides a publicly available benchmark dataset manually tagged against 6 classes. S…
Automated Feature EngineeringBIG-bench Machine LearningClassificationDeep Learning+7Sparse Sinkhorn Attention
We propose Sparse Sinkhorn Attention, a new efficient and sparse method for learning to attend. Our method is based on differentiable sorting of internal representations. Concretely, we introduce a meta sorting network t…
Document ClassificationImage GenerationLanguage ModelingLanguage Modelling+1Multilingual Twitter Corpus and Baselines for Evaluating Demographic Bias in Hate Speech Recognition
Existing research on fairness evaluation of document classification models mainly uses synthetic monolingual data without ground truth for author demographic attributes. In this work, we assemble and publish a multilingu…
Document ClassificationFairnessHate Speech Detectionspeech-recognition+1MAGNET: Multi-Label Text Classification using Attention-based Graph Neural Network
In Multi-Label Text Classification (MLTC), one sample can belong to more than one class. It is observed that most MLTC tasks, there are dependencies or correlations among labels. Existing methods tend to ignore the relat…
Document ClassificationGeneral ClassificationGraph AttentionGraph Neural Network+6A Systematic Comparison of Architectures for Document-Level Sentiment Classification
Documents are composed of smaller pieces - paragraphs, sentences, and tokens - that have complex relationships between one another. Sentiment classification models that take into account the structure inherent in these d…
ClassificationDocument ClassificationGeneral ClassificationLanguage Modeling+4Constrained Relational Topic Models
Relational topic models (RTM) have been widely used to discover hidden topics in a collection of networked documents. In this paper, we introduce the class of Constrained Relational Topic Models (CRTM), a semi-supervised…
Document ClassificationTopic ModelsOn the Replicability of Combining Word Embeddings and Retrieval Models
We replicate recent experiments attempting to demonstrate an attractive hypothesis about the use of the Fisher kernel framework and mixture models for aggregating word embeddings towards document representations and the …
ClusteringDocument ClassificationInformation RetrievalRetrieval+1Semantic Sensitive TF-IDF to Determine Word Relevance in Documents
Keyword extraction has received an increasing attention as an important research topic which can lead to have advancements in diverse applications such as document context categorization, text indexing and document class…
Document ClassificationKeyword ExtractionWord EmbeddingsRobust Cross-lingual Embeddings from Parallel Sentences
Recent advances in cross-lingual word embeddings have primarily relied on mapping-based methods, which project pretrained word embeddings from different languages into a shared space through a linear transformation. Howe…
Cross-Lingual Document ClassificationCross-Lingual Word EmbeddingsDocument ClassificationRetrieval+6PySS3: A Python package implementing a novel text classifier with visualization tools for Explainable AI
A recently introduced text classifier, called SS3, has obtained state-of-the-art performance on the CLEF's eRisk tasks. SS3 was created to deal with risk detection over text streams and, therefore, not only supports incr…
BIG-bench Machine LearningClassificationDocument ClassificationGeneral Classification+5Long-length Legal Document Classification
One of the principal tasks of machine learning with major applications is text classification. This paper focuses on the legal domain and, in particular, on the classification of lengthy legal documents. The main challen…
ClassificationDocument ClassificationDocument EmbeddingGeneral Classification+2