Papers Text Categorization
“Text Categorization” 태그가 달린 논문 247편 · 필터 해제
Text Ranking and Classification using Data Compression
A well-known but rarely used approach to text categorization uses conditional entropy estimates computed using data compression tools. Text affinity scores derived from compressed sizes can be used for classification and…
ClassificationData CompressionText CategorizationBDCN: Semantic Embedding Self-explanatory Breast Diagnostic Capsules Network
“Building an interpretable AI diagnosis system for breast cancer is an important embodiment ofAI assisted medicine. Traditional breast cancer diagnosis methods based on machine learning areeasy to explain but the accurac…
DiagnosticText Categorizationtext-classificationText ClassificationA comparison of latent semantic analysis and correspondence analysis of document-term matrices
Latent semantic analysis (LSA) and correspondence analysis (CA) are two techniques that use a singular value decomposition (SVD) for dimensionality reduction. LSA has been extensively used to obtain low-dimensional repre…
Authorship AttributionDimensionality ReductionDocument ClassificationText CategorizationBERT-based Chinese Text Classification for Emergency Domain with a Novel Loss Function
This paper proposes an automatic Chinese text categorization method for solving the emergency event report classification problem. Since bidirectional encoder representations from transformers (BERT) has achieved great s…
BenchmarkingGeneral ClassificationManagementText Categorization+2Clustering Word Embeddings with Self-Organizing Maps. Application on LaRoSeDa - A Large Romanian Sentiment Data Set
Romanian is one of the understudied languages in computational linguistics, with few resources available for the development of natural language processing tools. In this paper, we introduce LaRoSeDa, a Large Romanian Se…
ClusteringSentiment AnalysisSentiment ClassificationText Categorization+1Minimally-Supervised Structure-Rich Text Categorization via Learning on Text-Rich Networks
Text categorization is an essential task in Web content analysis. Considering the ever-evolving Web data and new emerging categories, instead of the laborious supervised setting, in this paper, we focus on the minimally-…
Product CategorizationText CategorizationClustering Word Embeddings with Self-Organizing Maps. Application on LaRoSeDa -- A Large Romanian Sentiment Data Set
Romanian is one of the understudied languages in computational linguistics, with few resources available for the development of natural language processing tools. In this paper, we introduce LaRoSeDa, a Large Romanian Se…
ClusteringSentiment AnalysisSentiment ClassificationText Categorization+1Infotec + CentroGEO at SemEval-2020 Task 8: Deep Learning and Text Categorization approach for Memes classification
The information shared on social media is increasingly important; both images and text, and maybe the most popular combination of these two kinds of data are the memes. This manuscript describes our participation in Memo…
Text CategorizationSMM4H Shared Task 2020 - A Hybrid Pipeline for Identifying Prescription Drug Abuse from Twitter: Machine Learning, Deep Learning, and Post-Processing
This paper presents our approach to multi-class text categorization of tweets mentioning prescription medications as being indicative of potential abuse/misuse (A), consumption/non-abuse (C), mention-only (M), or an unre…
Data AugmentationText CategorizationWord EmbeddingsImproving Arabic Text Categorization Using Transformer Training Diversification
Automatic categorization of short texts, such as news headlines and social media posts, has many applications ranging from content analysis to recommendation systems. In this paper, we use such text categorization i.e., …
Recommendation SystemsText CategorizationNatCat: Weakly Supervised Text Classification with Naturally Annotated Resources
We describe NatCat, a large-scale resource for text classification constructed from three data sources: Wikipedia, Stack Exchange, and Reddit. NatCat consists of document-category pairs derived from manual curation that …
ClassificationGeneral ClassificationText Categorizationtext-classification+1Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach
Tagging has been recognized as a successful practice to boost relevance matching for information retrieval (IR), especially when items lack rich textual descriptions. A lot of research has been done for either multi-labe…
Graph Neural NetworkInformation RetrievalLink PredictionMulti-Label Classification+4Deep learning models for representing out-of-vocabulary words
Communication has become increasingly dynamic with the popularization of social networks and applications that allow people to express themselves and communicate instantly. In this scenario, distributed representation mo…
Deep Learningnamed-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)+2Sequence-to-Set Semantic Tagging for Complex Query Reformulation and Automated Text Categorization in Biomedical IR using Self-Attention
Novel contexts, comprising a set of terms referring to one or more concepts, may often arise in complex querying scenarios such as in evidence-based medicine (EBM) involving biomedical literature. These may not explicitl…
RetrievalText CategorizationImprove 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+3Text Categorization for Conflict Event Annotation
We cast the problem of event annotation as one of text categorization, and compare state of the art text categorization techniques on event data produced within the Uppsala Conflict Data Program (UCDP). Annotating a sing…
Text CategorizationAn approach based on Combination of Features for automatic news retrieval
Nowadays, according to the increasingly increasing information, the importance of its presentation is also increasing. The internet has become one of the main sources of information for users and their favorite topics. I…
Information RetrievalNews RetrievalRetrievalText CategorizationSeMemNN: A Semantic Matrix-Based Memory Neural Network for Text Classification
Text categorization is the task of assigning labels to documents written in a natural language, and it has numerous real-world applications including sentiment analysis as well as traditional topic assignment tasks. In t…
ArticlesGeneral ClassificationSentiment AnalysisText Categorization+2A Machine Learning Framework for Authorship Identification From Texts
Authorship identification is a process in which the author of a text is identified. Most known literary texts can easily be attributed to a certain author because they are, for example, signed. Yet sometimes we find unfi…
BIG-bench Machine LearningInformation RetrievalRetrievalText CategorizationPySS3: 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+5