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Text Categorization

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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

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://bitbucket.org/luisespinosa/seven

공식 코드

SeVeN: Augmenting Word Embeddings with Unsupervised Relation Vectors

https://github.com/AKC23/Harnessing-LLMs-over-transformer-models-for-detecting-Bengali-depressive-text-A-comprehensive-study

공식 코드

Harnessing Large Language Models Over Transformer Models for Detecting Bengali Depressive Social Media Text: A Comprehensive Study

https://github.com/CZFuChason/SeMemNN

공식 코드

SeMemNN: A Semantic Matrix-Based Memory Neural Network for Text Classification

https://github.com/CliffordLai/eqc

공식 코드

Ensemble Quantile Classifier

https://github.com/INGEOTEC/microTC

공식 코드

An Automated Text Categorization Framework based on Hyperparameter Optimization

https://github.com/ZeweiChu/NatCat

공식 코드

NatCat: Weakly Supervised Text Classification with Naturally Annotated Resources

https://github.com/ancatache/LaRoSeDa

공식 코드

Clustering Word Embeddings with Self-Organizing Maps. Application on LaRoSeDa -- A Large Romanian Sentiment Data Set

https://github.com/cair/TextUnderstandingTsetlinMachine

공식 코드

Using the Tsetlin Machine to Learn Human-Interpretable Rules for High-Accuracy Text Categorization with Medical Applications

https://github.com/catalinstoean/FCGR-LR

공식 코드

Authorship Attribution Using the Chaos Game Representation

https://github.com/facebookresearch/zest

공식 코드

Text Ranking and Classification using Data Compression

https://github.com/giannisnik/repset

공식 코드

Rep the Set: Neural Networks for Learning Set Representations

https://github.com/gugarosa/mh_fine_tuning

공식 코드

Improving Pre-Trained Weights Through Meta-Heuristics Fine-Tuning

https://github.com/iesl/leopard

공식 코드

Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks

https://github.com/jiyfeng/disco4textcat

공식 코드

Neural Discourse Structure for Text Categorization

https://github.com/levelfour/pumil

공식 코드

Convex Formulation of Multiple Instance Learning from Positive and Unlabeled Bags

https://github.com/pedrada88/preproc-textclassification

공식 코드

On the Role of Text Preprocessing in Neural Network Architectures: An Evaluation Study on Text Categorization and Sentiment Analysis

https://github.com/pgcool/iDocNADE

공식 코드

Document Informed Neural Autoregressive Topic Models

https://github.com/rturrisige/textclassification

공식 코드

Beyond original Research Articles Categorization via NLP

https://github.com/sergioburdisso/pyss3

공식 코드

t-SS3: a text classifier with dynamic n-grams for early risk detection over text streams

https://github.com/vgupta123/SCDV-MS

공식 코드

Improving Document Classification with Multi-Sense Embeddings

https://github.com/HongyangGao/hConv-gPool-Net

Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations

https://github.com/M-S-ALAM/Sarcastic-Comment-Detection

A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks

https://github.com/NamanJain2050/sarcasm-detection

A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks

https://github.com/NamanJain2050/semeval-2014-task-9

A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks

https://github.com/airi-institute/al_toolbox

A Sequential Algorithm for Training Text Classifiers

https://github.com/avyavkumar/few-shot-learning-notebooks

Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks

https://github.com/changji2069/Scope-Project

On the Role of Text Preprocessing in Neural Network Architectures: An Evaluation Study on Text Categorization and Sentiment Analysis

https://github.com/changji2069/literature-review

On the Role of Text Preprocessing in Neural Network Architectures: An Evaluation Study on Text Categorization and Sentiment Analysis

https://github.com/hc495/staicc

Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales

https://github.com/ht1221/leap-lstm

Leap-LSTM: Enhancing Long Short-Term Memory for Text Categorization

https://github.com/idiap/mhan

Massively Multilingual Word Embeddings

https://github.com/jonjoncardoso/jonjoncardoso

Very Large Language Model as a Unified Methodology of Text Mining

https://github.com/kyriemao/TagGNN-SIGIR

Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach

https://github.com/qampspring2023/qgpt-issue-31

Quantum Recurrent Neural Networks for Sequential Learning

https://github.com/textvec/textvec

Inverse-Category-Frequency based supervised term weighting scheme for text categorization

https://github.com/zveryansky/textvec

Inverse-Category-Frequency based supervised term weighting scheme for text categorization

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