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Клъстеризация на документи×Извличане на ключови думи×Тематичен анализ×
ОбластИзвличане на текстИзвличане на текстКачествени изследвания
СемействоProcess / pipelineProcess / pipelineProcess / pipeline
Година на възникване2006
СъздателVirginia Braun and Victoria Clarke
ТипUnsupervised text-mining taskNLP text-mining taskMethod
Основополагащ източникAggarwal, C. C. & Zhai, C. (2012). Mining Text Data. Springer. ISBN: 9781461432227Mihalcea, R. & Tarau, P. (2004). TextRank: Bringing Order into Texts. EMNLP, 404-411. link ↗Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. DOI ↗
Други названияtext clustering, unsupervised text grouping, Belge Kümeleme (Document Clustering)keyphrase extraction, key term extraction, Anahtar Kelime Çıkarma (Keyword Extraction)TA, Reflexive Thematic Analysis
Свързани443
РезюмеDocument clustering is an unsupervised text-mining task that groups documents with similar content together without using any labels. It is used to organise large collections and for exploratory analysis, drawing on the body of text-mining techniques consolidated by Aggarwal and Zhai (2012) and compared empirically by Steinbach, Karypis and Kumar (2000).Keyword extraction is a natural-language-processing task that automatically identifies the words or phrases that best represent the content of a document. It turns a body of free text into a compact, ranked list of key terms, drawing on statistical, graph-based methods such as TextRank (Mihalcea & Tarau, 2004), or embedding-based methods such as KeyBERT (Grootendorst, 2020).Thematic Analysis (TA) is a qualitative research methodology for identifying, analyzing, and reporting patterns (themes) in qualitative data. Developed systematically by Virginia Braun and Victoria Clarke (2006), TA is flexible and accessible, applicable across diverse theoretical frameworks and data types, making it one of the most widely used qualitative methods in psychology, health research, and social sciences.
ScholarGateНабор от данни
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  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 2 Източници
  3. PUBLISHED
  1. v1
  2. 3 Източници
  3. PUBLISHED

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ScholarGateСравнение на методи: Document Clustering · Keyword Extraction · Thematic Analysis. Извлечено на 2026-06-19 от https://scholargate.app/bg/compare