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Identifikace jazyka (LID)×Analýza sentimentu×Segmentace textu×
OborDolování textuDolování textuDolování textu
RodinaProcess / pipelineProcess / pipelineProcess / pipeline
Rok vzniku1997
TvůrceMarti A. Hearst (TextTiling)
TypNLP text-classification taskNLP text-classification taskNLP document-structure / topic-boundary detection
Původní zdrojLui, M. & Baldwin, T. (2012). langid.py: An Off-the-shelf Language Identification Tool. Proceedings of the ACL 2012 System Demonstrations. link ↗Pang, B. & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval, 2(1-2), 1-135. DOI ↗Hearst, M.A. (1997). TextTiling: Segmenting Text into Multi-Paragraph Subtopic Passages. Computational Linguistics, 23(1), 33-64. link ↗
Další názvylanguage detection, LID, Dil Tanımlama (Language Identification)opinion mining, polarity detection, duygu analizitopic segmentation, discourse segmentation, linear text segmentation, Metin Bölümleme (Text Segmentation)
Příbuzné434
ShrnutíLanguage identification is a natural-language-processing task that automatically detects which language a piece of text is written in. Building on off-the-shelf tools such as langid.py (Lui & Baldwin, 2012) and the efficient classifiers of Joulin et al. (2017), it is widely used to preprocess and filter multilingual data sets.Sentiment analysis, also called opinion mining, is a natural-language-processing task that detects the emotional tone of text — typically classifying it as positive, negative, or neutral. It turns unstructured opinion text into structured, quantifiable polarity signals using one of three families of approaches: sentiment lexicons, trained machine-learning classifiers, or pretrained transformer models.Text segmentation divides a long document into meaningful sections (segments) along topic or discourse boundaries. Introduced for subtopic passages by Marti A. Hearst's TextTiling (1997), it supports document-structure analysis and the detection of topic transitions in continuous text.
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ScholarGatePorovnat metody: Language Identification · Sentiment Analysis · Text Segmentation. Získáno 2026-06-17 z https://scholargate.app/cs/compare