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.
Original languageEnglish
Title of host publication Internet and Modern Society. Human-Computer Communication
PublisherSpringer Nature
Pages105-112
Number of pages8
ISBN (Print)9783031961762
DOIs
StatePublished - 2026
EventInternet and Modern Society – IMS-2024 - ИТМО-Университет, Санкт-Петербург, Russian Federation
Duration: 24 Jun 202426 Jun 2024
Conference number: XXVII
https://ims.itmo.ru
https://ims.itmo.ru/
https://ims.itmo.ru

Publication series

NameCommunications in Computer and Information Science
Volume2534 CCIS

Conference

ConferenceInternet and Modern Society – IMS-2024
Abbreviated titleIMS 2024
Country/TerritoryRussian Federation
CityСанкт-Петербург
Period24/06/2426/06/24
Internet address

    Research areas

  • 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

ID: 151442754