Process / pipeline

Text Classification — Text Categorization

Text classification, also called text categorization, is a supervised natural-language-processing task that automatically assigns documents to predefined categories. Building on the support-vector-machine approach to text categorization established by Joachims (1998) and consolidated in the text-mining literature by Aggarwal and Zhai (2012), it powers tasks such as spam detection and topic classification by learning from labelled examples.

MethodMind'de açSoonVideoSoon

Tam yöntemi oku

Members only

Sources

Joachims, T. (1998). Text Categorization with Support Vector Machines: Learning with Many Relevant Features. ECML 1998. Lecture Notes in Computer Science, vol 1398. Springer. DOI: 10.1007/BFb0026683 ↗
Aggarwal, C. C. & Zhai, C. (2012). Mining Text Data. Springer. ISBN: 978-1-4614-3222-7

Referenced by

Argument Mining Aspect-Based Sentiment Analysis Authorship Attribution Automated Essay Scoring Automatic Text Evaluation Clinical Text Mining Content Analysis Contrastive Learning for NLP Cross-lingual Text Analysis Dialogue Act Classification Discourse Parsing Doc2Vec Domain Adaptation Emotion Detection Event Detection Explainable LDA Topic Model Fake News Detection Few-Shot Text Classification Gender Bias Detection Hallucination Detection Hate Speech Detection Implicit Sentiment Analysis Intent Detection Language Identification Linguistic Acceptability Assessment Machine Reading Comprehension Multi-Document Summarization N-gram Language Model Named Entity Recognition Opinion Mining Paraphrase Detection Prompt Engineering Propaganda Detection Question Answering Readability Analysis Relation Extraction Self-supervised Sentiment Analysis Semantic Parsing Sentiment Analysis Slot Filling Social Media NLP Speculation Detection Stance Detection Subjectivity Detection Text Coherence Scoring Text Deduplication Text Infilling Text Regression Textual Entailment TF-IDF Timeline Extraction Word2Vec Zero-Shot Classification

Bu sayfada bir hata mı var? Bildir / düzeltme öner →

Tam yöntemi oku

Sources

Related methods

Referenced by