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Text Preprocessing for Keyword and Key Phrase Extraction. / Troshina, A.

Internet and Modern Society. Human-Computer Communication . Springer Nature, 2026. стр. 105-112 (Communications in Computer and Information Science; Том 2534 CCIS).

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Harvard

Troshina, A 2026, Text Preprocessing for Keyword and Key Phrase Extraction. в Internet and Modern Society. Human-Computer Communication . Communications in Computer and Information Science, Том. 2534 CCIS, Springer Nature, стр. 105-112, XXVII Международная объединенная научная конференция «Интернет и современное общество», Санкт-Петербург, Российская Федерация, 24/06/24. https://doi.org/10.1007/978-3-031-96177-9_9

APA

Troshina, A. (2026). Text Preprocessing for Keyword and Key Phrase Extraction. в Internet and Modern Society. Human-Computer Communication (стр. 105-112). (Communications in Computer and Information Science; Том 2534 CCIS). Springer Nature. https://doi.org/10.1007/978-3-031-96177-9_9

Vancouver

Troshina A. Text Preprocessing for Keyword and Key Phrase Extraction. в Internet and Modern Society. Human-Computer Communication . Springer Nature. 2026. стр. 105-112. (Communications in Computer and Information Science). https://doi.org/10.1007/978-3-031-96177-9_9

Author

Troshina, A. / Text Preprocessing for Keyword and Key Phrase Extraction. Internet and Modern Society. Human-Computer Communication . Springer Nature, 2026. стр. 105-112 (Communications in Computer and Information Science).

BibTeX

@inproceedings{f71e07bc5fb54170897c107fc1fa7d09,
title = "Text Preprocessing for Keyword and Key Phrase Extraction",
abstract = "This article explores various text preprocessing techniques for the extraction of keywords and key phrases. It delves into methods such as text lemmatization, stop-word removal, and number removal, comparing their efficacy with unprocessed text in keyword extraction. Evaluation is based on the ability of keyword sets to retrieve relevant news articles from search engine queries. The study employs multiple keyword extraction tools for comprehensive analysis. {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.",
keywords = "Keyword Extraction, Lemmatization, Search Engine, Stop-Word Removal, Text Preprocessing, Extraction, Information management, Query processing, Text processing, Key-phrase, Key-phrases extractions, Keywords extraction, News articles, Pre-processing techniques, Stop word, Stop-word removal, Text preprocessing, Word removals, Search engines",
author = "A. Troshina",
note = "Export Date: 29 March 2026; Cited By: 0; Correspondence Address: A. Troshina; St Petersburg State University, St. Petersburg, Russian Federation; email: troshina26@mail.ru; Conference name: 27th International Conference on Internet and Modern Society, IMS 2024; Conference date: 24 June 2024 through 26 June 2024; Conference code: 339649; null ; Conference date: 24-06-2024 Through 26-06-2024",
year = "2026",
doi = "10.1007/978-3-031-96177-9_9",
language = "Английский",
isbn = "9783031961762",
series = "Communications in Computer and Information Science",
publisher = "Springer Nature",
pages = "105--112",
booktitle = "Internet and Modern Society. Human-Computer Communication",
address = "Германия",
url = "https://ims.itmo.ru , https://ims.itmo.ru/, https://ims.itmo.ru",

}

RIS

TY - GEN

T1 - Text Preprocessing for Keyword and Key Phrase Extraction

AU - Troshina, A.

N1 - Conference code: XXVII

PY - 2026

Y1 - 2026

N2 - This article explores various text preprocessing techniques for the extraction of keywords and key phrases. It delves into methods such as text lemmatization, stop-word removal, and number removal, comparing their efficacy with unprocessed text in keyword extraction. Evaluation is based on the ability of keyword sets to retrieve relevant news articles from search engine queries. The study employs multiple keyword extraction tools for comprehensive analysis. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

AB - This article explores various text preprocessing techniques for the extraction of keywords and key phrases. It delves into methods such as text lemmatization, stop-word removal, and number removal, comparing their efficacy with unprocessed text in keyword extraction. Evaluation is based on the ability of keyword sets to retrieve relevant news articles from search engine queries. The study employs multiple keyword extraction tools for comprehensive analysis. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

KW - Keyword Extraction

KW - Lemmatization

KW - Search Engine

KW - Stop-Word Removal

KW - Text Preprocessing

KW - Extraction

KW - Information management

KW - Query processing

KW - Text processing

KW - Key-phrase

KW - Key-phrases extractions

KW - Keywords extraction

KW - News articles

KW - Pre-processing techniques

KW - Stop word

KW - Stop-word removal

KW - Text preprocessing

KW - Word removals

KW - Search engines

UR - https://www.mendeley.com/catalogue/e3efd923-3237-3b7f-905c-7df86fee7629/

U2 - 10.1007/978-3-031-96177-9_9

DO - 10.1007/978-3-031-96177-9_9

M3 - статья в сборнике материалов конференции

SN - 9783031961762

T3 - Communications in Computer and Information Science

SP - 105

EP - 112

BT - Internet and Modern Society. Human-Computer Communication

PB - Springer Nature

Y2 - 24 June 2024 through 26 June 2024

ER -

ID: 151442754