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Wyświetlanie 1-2 z 2
Tytuł:
Identification of the leading research domains and grouping of articles on the smart city using text mining
Autorzy:
Zdonek, Dariusz
Powiązania:
https://bibliotekanauki.pl/articles/1927445.pdf
Data publikacji:
2020
Wydawca:
Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
Tematy:
smart city
text mining
information and communication technology
scientific paper
research areas
technologia informacyjna
technologia komunikacyjna
referat naukowy
obszar badawczy
Opis:
Purpose: The objective of the paper is to use text mining to identify leading research domains concerning the smart city following an analysis of research articles with a high citation index according to the Web of Science. Design/methodology/approach: An original method is proposed for analysing academic texts using the R language, tokenisation, lemmatisation, n-grams and correspondence analysis. The author analysed fifty of the most cited articles indexed in the Web of Science from 2014 to 2019. Findings: The paper presents the advantages and drawbacks of the proposed method of analysing research publications. The assets include automation and repeatability of the analysis of a large number of documents and improved knowledge about links among the articles in terms of research domains. The disadvantage is the loss of information from diagrams and figures. The method identified two leading research domains related to the notion of the smart city, technologies and systems. The analysed publications were categorised by selected keywords. Research limitations/implications: Future work should include further refinement of the assumptions for the method, analyses of a more significant number of research texts and a narrowing down of the domain of the smart city. It is desirable to consider other functional domains of the city, such as energy, public health, environmental protection or transport. Practical implications: The proposed method can complement a standard literature analysis regarding the smart city. The leading research domains related to the smart city in the analysed articles were systems and technologies employed to improve how the city operates. Social implications: Text mining can be employed by various experts focusing on the smart city and constitutes a refreshing complement for other research methods, such as questionnaire surveys, interviews or observations. Originality/value The publication can be useful for researchers from various fields and managers seeking to create and use simple, useful methods and tools for analysing unstructured text documents for decision-making. The paper proposes a separate text mining analysis of abstracts and whole documents using n-grams. This yielded a more precise list of areas relevant to the smart city. The grouping was done using correspondence analysis of the fifty most cited articles indexed in the Web of Science from 2014 to 2019.
Źródło:
Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska; 2020, 148; 845-860
1641-3466
Pojawia się w:
Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Identification of technologies in Industry 4.0 with the use of text mining
Autorzy:
Zdonek, Dariusz
Powiązania:
https://bibliotekanauki.pl/articles/1931589.pdf
Data publikacji:
2020
Wydawca:
Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
Tematy:
text mining
Industry 4.0
information and communication technology
scientific paper
eksploracja tekstu
Przemysł 4.0
technologie informacyjne i komunikacyjne
praca naukowa
Opis:
Purpose: The objective of this paper is to identify leading technologies in Industry 4.0. Design/methodology/approach: The identification was made with the use of text mining to explore the scientific texts in this field. Assumptions of own iterative method for analyzing scientific texts were proposed, with the use of R language, tokenization, lemmatization, n-grams and correspondence analysis. The assumptions of the proposed method were used to analyze the 40 most often quoted articles indexed in the Web of Science. Findings: On the basis of the obtained results, 4 leading technologies were identified. These are Cloud Computing, Internet of Things, Cyber-physical System and Big Data. Originality/value: The article proposes an original method of identifying the leading technologies used in Industry 4.0. The proposed method is based on text mining and correspondence analysis.
Źródło:
Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska; 2020, 142; 45-57
1641-3466
Pojawia się w:
Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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