Papers Document Classification
“Document Classification” 태그가 달린 논문 670편 · 필터 해제
Modular Multimodal Architecture for Document Classification
Page classification is a crucial component to any document analysis system, allowing for complex branching control flows for different components of a given document. Utilizing both the visual and textual content of a pa…
ClassificationDocument ClassificationGeneral ClassificationSpeeding up Word Mover's Distance and its variants via properties of distances between embeddings
The Word Mover's Distance (WMD) proposed by Kusner et al. is a distance between documents that takes advantage of semantic relations among words that are captured by their embeddings. This distance proved to be quite eff…
Document ClassificationGeneral ClassificationFLATM: A Fuzzy Logic Approach Topic Model for Medical Documents
One of the challenges for text analysis in medical domains is analyzing large-scale medical documents. As a consequence, finding relevant documents has become more difficult. One of the popular methods to retrieve inform…
ClusteringDocument ClassificationTopic ModelsMy Approach = Your Apparatus? Entropy-Based Topic Modeling on Multiple Domain-Specific Text Collections
Comparative text mining extends from genre analysis and political bias detection to the revelation of cultural and geographic differences, through to the search for prior art across patents and scientific papers. These a…
ArticlesBias DetectionClusteringDocument Classification+1Improving Document Classification with Multi-Sense Embeddings
Efficient representation of text documents is an important building block in many NLP tasks. Research on long text categorization has shown that simple weighted averaging of word vectors for sentence representation often…
ClassificationClusteringDocument ClassificationGeneral Classification+3Asynchronous Distributed Learning from Constraints
In this paper, the extension of the framework of Learning from Constraints (LfC) to a distributed setting where multiple parties, connected over the network, contribute to the learning process is studied. LfC relies on t…
Document ClassificationPrivacy PreservingLexiPers: An ontology based sentiment lexicon for Persian
Sentiment analysis refers to the use of natural language processing to identify and extract subjective information from textual resources. One approach for sentiment extraction is using a sentiment lexicon. A sentiment l…
Document ClassificationGeneral ClassificationSentiment Analysist-SS3: a text classifier with dynamic n-grams for early risk detection over text streams
A recently introduced classifier, called SS3, has shown to be well suited to deal with early risk detection (ERD) problems on text streams. It obtained state-of-the-art performance on early depression and anorexia detect…
Anorexia DetectionClassificationDocument ClassificationGeneral Classification+4ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations
The pre-training of text encoders normally processes text as a sequence of tokens corresponding to small text units, such as word pieces in English and characters in Chinese. It omits information carried by larger text g…
Chinese Named Entity RecognitionChinese Word SegmentationDocument ClassificationNatural Language Inference+3Keeping Consistency of Sentence Generation and Document Classification with Multi-Task Learning
The automated generation of information indicating the characteristics of articles such as headlines, key phrases, summaries and categories helps writers to alleviate their workload. Previous research has tackled these t…
Abstractive Text SummarizationArticlesDocument ClassificationGeneral Classification+2PRADO: Projection Attention Networks for Document Classification On-Device
Recently, there has been a great interest in the development of small and accurate neural networks that run entirely on devices such as mobile phones, smart watches and IoT. This enables user privacy, consistent user exp…
ClassificationDocument ClassificationDocument Text ClassificationGeneral Classification+3Phenotyping of Clinical Notes with Improved Document Classification Models Using Contextualized Neural Language Models
Clinical notes contain an extensive record of a patient's health status, such as smoking status or the presence of heart conditions. However, this detail is not replicated within the structured data of electronic health …
Document ClassificationGeneral ClassificationWasserstein distances for evaluating cross-lingual embeddings
Word embeddings are high dimensional vector representations of words that capture their semantic similarity in the vector space. There exist several algorithms for learning such embeddings both for a single language as w…
Cross-Lingual Document ClassificationDocument ClassificationRetrievalSemantic Similarity+2DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters
We propose a novel spectral convolutional neural network (CNN) model on graph structured data, namely Distributed Feedback-Looped Networks (DFNets). This model is incorporated with a robust class of spectral graph filter…
Document ClassificationGeneral ClassificationNode ClassificationHierarchical Transformers for Long Document Classification
BERT, which stands for Bidirectional Encoder Representations from Transformers, is a recently introduced language representation model based upon the transfer learning paradigm. We extend its fine-tuning procedure to add…
ClassificationDocument ClassificationGeneral ClassificationTopic Classification+1Progress Notes Classification and Keyword Extraction using Attention-based Deep Learning Models with BERT
Various deep learning algorithms have been developed to analyze different types of clinical data including clinical text classification and extracting information from 'free text' and so on. However, automate the keyword…
ClassificationDeep LearningDocument ClassificationGeneral Classification+3Learning Only from Relevant Keywords and Unlabeled Documents
We consider a document classification problem where document labels are absent but only relevant keywords of a target class and unlabeled documents are given. Although heuristic methods based on pseudo-labeling have been…
Document ClassificationGeneral Classificationtext-classificationText ClassificationADAPTING PRETRAINED LANGUAGE MODELS FOR LONG DOCUMENT CLASSIFICATION
Pretrained language models (LMs) have shown excellent results in achieving human like performance on many language tasks. However, the most powerful LMs have one significant drawback: a fixed-sized input. With this const…
ClassificationDocument ClassificationNeural Generative Rhetorical Structure Parsing
Rhetorical structure trees have been shown to be useful for several document-level tasks including summarization and document classification. Previous approaches to RST parsing have used discriminative models; however, t…
Document ClassificationEnriching BERT with Knowledge Graph Embeddings for Document Classification
In this paper, we focus on the classification of books using short descriptive texts (cover blurbs) and additional metadata. Building upon BERT, a deep neural language model, we demonstrate how to combine text representa…
ClassificationDescriptiveDocument ClassificationGeneral Classification+3