Implementation Of Sequential Pattern Algorithms In Web Usage Mining.

Sequential pattern mining is a data-mining technique used for determining time-related behaviour in sequential databases. The information extracted from sequential pattern mining can be used in marketing fields, medical records, sales analysis, and so on. Several algorithms for maintaining sequentia...

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Publicado en:Turkish Journal of Physiotherapy Rehabilitation Vol. 32; no. 2; pp. 539 - 546
Autores principales: Aruna, V., Singh, Harsh Pratap, Sujatha, D.
Formato: tables/charts Journal Article
Publicado: Turkish Journal of Physiotherapy & Rehabilitation 2021
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Implementation Of Sequential Pattern Algorithms In Web Usage Mining.
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          Aruna, V.
          Singh, Harsh Pratap
          Sujatha, D.
        affil: Research Scholar, Dept. of Computer Science & Engineering, Sri Satya Sai University of Technology & Medical Sciences, Sehore, Bhopal-Indore Road, MadhyaPradesh, India
      sug:
        subj:
          Data Mining Methods
          Data Mining Utilization
          Algorithms
          World Wide Web
          Marketing
          Medical Records
          Access to Information
          Models, Statistical
          Data Analytics
          Information Retrieval
      ab: Sequential pattern mining is a data-mining technique used for determining time-related behaviour in sequential databases. The information extracted from sequential pattern mining can be used in marketing fields, medical records, sales analysis, and so on. Several algorithms for maintaining sequential patterns have been developed. Although there have been many recent updates on the sequential patterns in static database. The complexity of sequential pattern mining increases in the dynamic database because of the insertion of new data sets. This paper characterizing sequential pattern-mining algorithms based on significant key highlights upheld by the strategies. This paper targets comprehension of sequential pattern mining issues.
      pubtype: Academic Journal
      doctype:
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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