Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Анализ совместной встречаемости× | TF-IDF× | |
|---|---|---|
| Область | Интеллектуальный анализ текста | Интеллектуальный анализ текста |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1957 | 1988 |
| Автор метода≠ | J.R. Firth (distributional principle) | Salton & Buckley |
| Тип≠ | Text-mining / distributional-semantics technique | Text vectorization / term-weighting scheme |
| Основополагающий источник≠ | Firth, J.R. (1957). A Synopsis of Linguistic Theory. Studies in Linguistic Analysis. Oxford: Blackwell. link ↗ | Salton, G. & Buckley, C. (1988). Term-weighting approaches in automatic text retrieval. Information Processing & Management, 24(5), 513-523. DOI ↗ |
| Другие названия | word co-occurrence, co-occurrence network, Kelime Eş-Oluşum Analizi | term weighting, tf-idf weighting, TF-IDF Vektörizasyonu |
| Связанные≠ | 4 | 3 |
| Сводка≠ | Co-occurrence analysis is a text-mining technique that statistically counts the word pairs that appear together within a window or a sentence and uses their frequencies to reveal semantic maps and thematic structure. It rests on the distributional principle articulated by J.R. Firth in 1957 — that a word is characterised by the company it keeps. | 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. |
| ScholarGateНабор данных ↗ |
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