Research trends on big data domain using text mining algorithms.

Most of the theories have considered big data as an interesting subject in the information technology domain. Big data is a term for describing huge databases that traditional methods in data processing suffer from analyzing them. Recognizing and clustering emerging topics in this area will help res...

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Publicado en:Digital Scholarship in the Humanities Vol. 36; no. 2; pp. 361 - 371
Autores principales: Jalali, Seyed Mohammad Jafar, Park, Han Woo, Vanani, Iman Raeesi, Pho, Kim-Hung
Formato: Artículo
Publicado: Oxford University Press / USA Jun2021
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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          Jalali, Seyed Mohammad Jafar
          Park, Han Woo
          Vanani, Iman Raeesi
          Pho, Kim-Hung
        affil:
          Institute for Intelligent Systems Research and Innovation (IISRI), Deakin University , Waurn Ponds, Australia
          Department of Media and Communication, Interdisciplinary Program of Digital Convergence Business, Cyber Emotions Research Center, YeungNam University , Gyeongsan-si, South Korea
          Department of Industrial Management, Faculty of Management, Allameh Tabatabai University , Tehran, Iran
          Fractional Calculus, Optimization and Algebra Research Group, Faculty of Mathematics and Statistics, Ton Duc Thang University , Ho Chi Minh City, Vietnam
      su:
        Big data
        Social network analysis
        Algorithms
        Electronic data processing
      sug:
        subj:
          Big data
          Social network analysis
          Algorithms
          Electronic data processing
      ab: Most of the theories have considered big data as an interesting subject in the information technology domain. Big data is a term for describing huge databases that traditional methods in data processing suffer from analyzing them. Recognizing and clustering emerging topics in this area will help researchers whose aim is to work on this interesting subject. Text mining and social network analysis algorithms are utilized for identifying the emerging trends for big data domain. In this study, at first, we gathered the whole papers that are relevant to big data domain and then the word co-occurrence network was created based on the extracted keywords. Then the best clusters were identified and the relationship between keywords was recognized by the association rules technique. In conclusion, some suggestions were mentioned for future studies.
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    language: English
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