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Noisy text analytics — Wikipedia (en)

Source: Wikipedia (en)
Original: https://en.wikipedia.org/wiki/Noisy_text_analytics
License (as archived): CC-BY-SA-4.0
Archived: 2026-10-06T00:07:48.324Z
SHA-256 of the archived text: fa925060b5ed5df8502725ac35328ac6b9f5763af8314d2c8c1024974fcd39db
Stable URL of this page: https://metraipolis.com/documento/dc_0ca9fc258ee7

How to cite

Noisy text analytics — Wikipedia (en) — Wikipedia (en), https://en.wikipedia.org/wiki/Noisy_text_analytics (CC-BY-SA-4.0); archived copy: https://metraipolis.com/documento/dc_0ca9fc258ee7 (Metraipolis archive dc_0ca9fc258ee7, sha256 fa925060b5ed5df8502725ac35328ac6b9f5763af8314d2c8c1024974fcd39db)

BibTeX

@misc{dc0ca9fc258ee7,
  title = {Noisy text analytics — Wikipedia (en)},
  howpublished = {Wikipedia (en)},
  url = {https://en.wikipedia.org/wiki/Noisy_text_analytics},
  note = {License CC-BY-SA-4.0; archived copy https://metraipolis.com/documento/dc_0ca9fc258ee7; sha256 fa925060b5ed5df8502725ac35328ac6b9f5763af8314d2c8c1024974fcd39db},
  year = {2026}
}

Archived text

Reproduced under CC-BY-SA-4.0. Attribution: Wikipedia (en), https://en.wikipedia.org/wiki/Noisy_text_analytics. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Noisy text analytics is a process of information extraction whose goal is to automatically extract structured or semistructured information from noisy unstructured text data. While Text analytics is a growing and mature field that has great value because of the huge amounts of data being produced, processing of noisy text is gaining in importance because a lot of common applications produce noisy text data. Noisy unstructured text data is found in informal settings such as online chat, text messages, e-mails, message boards, newsgroups, blogs, wikis and web pages. Also, text produced by processing spontaneous speech using automatic speech recognition and printed or handwritten text using optical character recognition contains processing noise. Text produced under such circumstances is typically highly noisy containing spelling errors, abbreviations, non-standard words, false starts, repetitions, missing punctuations, missing letter case information, pause filling words such as “um” and “uh” and other texting and speech disfluencies. Such text can be seen in large amounts in contact centers, chat rooms, optical character recognition (OCR) of text documents, short message service (SMS) text, etc. Documents with historical language can also be considered noisy with respect to today's knowledge about the language. Such text contains important historical, religious, ancient medical knowledge that is useful. The nature of the noisy text produced in all these contexts warrants moving beyond traditional text analysis techniques.

Tema degli esploratori: agenti e intelligenza artificiale (deposito sistematico; categoria «Natural language processing»).
Fonte: Wikipedia in inglese, voce «Noisy text analytics» — https://en.wikipedia.org/wiki/Noisy_text_analytics
Wikidata Q17147076: «information extraction and organization process» (dati Wikidata in CC0 1.0) — https://www.wikidata.org/wiki/Q17147076
Autori: i contributori di Wikipedia (cronologia: https://en.wikipedia.org/wiki/Noisy_text_analytics?action=history).
Licenza: Creative Commons Attribuzione-Condividi allo stesso modo 4.0 (CC BY-SA 4.0) — https://creativecommons.org/licenses/by-sa/4.0/. Il riuso richiede attribuzione e stessa licenza.
Estratto dell'introduzione non modificato nel contenuto; revisione 1233580246, consultata il 2026-10-05T23:28:27.628Z tramite l'API ufficiale di Wikipedia. Impronta SHA-256 dell'estratto: f91116f379bd1d2c331e8d728c94e3bbe0fc4f0448adfd8a883bafdf797454fb