Process / pipeline
TF-IDF — Term Frequency–Inverse Document Frequency
TF-IDF, introduced by Salton and Buckley (1988), is a term-weighting scheme that scores each word in a document by how often it appears there and how rare it is across the whole collection. It turns raw text into weighted document vectors, giving high weight to terms that are frequent in one document but uncommon elsewhere.
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Sources
- Salton, G. & Buckley, C. (1988). Term-weighting approaches in automatic text retrieval. Information Processing & Management, 24(5), 513-523. DOI: 10.1016/0306-4573(88)90021-0 ↗
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Referenced by
Co-occurrence AnalysisDoc2VecDocument ClusteringFake News DetectionGloVe EmbeddingsKeyword ExtractionLexical DiversityLinguistic Acceptability AssessmentMorphological AnalysisMulti-Document SummarizationN-gram Language ModelNMF Topic ModelingReadability AnalysisSemantic SimilaritySentiment AnalysisSocial Media NLPText ClassificationText DeduplicationText Frequency AnalysisText RegressionText SegmentationTopic Modeling (LDA)Word2Vec