Text Categorization
41 papers with code • 0 benchmarks • 6 datasets
Text Categorization is the task of automatically assigning pre-defined categories to documents written in natural languages. Several types of Text Categorization have been studied, each of which deals with different types of documents and categories, such as topic categorization to detect discussed topics (e.g., sports, politics), spam detection, and sentiment classification to determine the sentiment typically in product or movie reviews.
Source: Effective Use of Word Order for Text Categorization with Convolutional Neural Networks
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Effects of term weighting approach with and without stop words removing on Arabic text classification
Text documents must be prepared and represented in a way that is appropriate for the algorithms used for data mining prior to classification.
Improving Large-Scale k-Nearest Neighbor Text Categorization with Label Autoencoders
In this paper, we introduce a multi-label lazy learning approach to deal with automatic semantic indexing in large document collections in the presence of complex and structured label vocabularies with high inter-label correlation.
Text Categorization Can Enhance Domain-Agnostic Stopword Extraction
This paper investigates the role of text categorization in streamlining stopword extraction in natural language processing (NLP), specifically focusing on nine African languages alongside French.
Harnessing Large Language Models Over Transformer Models for Detecting Bengali Depressive Social Media Text: A Comprehensive Study
The study categorized Reddit and X datasets into "Depressive" and "Non-Depressive" segments, translated into Bengali by native speakers with expertise in mental health, resulting in the creation of the Bengali Social Media Depressive Dataset (BSMDD).
Consistent Text Categorization using Data Augmentation in e-Commerce
In this work, we aim to improve an existing product categorization model that is already in use by a major web company, serving multiple applications.
Tuning Traditional Language Processing Approaches for Pashto Text Classification
However, the need for an automatic text categorization system for local languages is felt.
SA-CNN: Application to text categorization issues using simulated annealing-based convolutional neural network optimization
Convolutional neural networks (CNNs) are a representative class of deep learning algorithms including convolutional computation that perform translation-invariant classification of input data based on their hierarchical architecture.
Supervised and Unsupervised Categorization of an Imbalanced Italian Crime News Dataset
The scope of this paper is to explore the use of word embeddings for Italian crime news text categorization.
High-performance automatic categorization and attribution of inventory catalogs
Techniques of machine learning for automatic text categorization are applied and adapted for the problem of inventory catalog data attribution, with different approaches explored and optimal solution addressing the tradeoff between accuracy and performance is selected.
Monitoring Energy Trends through Automatic Information Extraction
Energy research is of crucial public importance but the use of computer science technologies like automatic text processing and data management for the energy domain is still rare.