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Improvements of Automatic Extraction of FA Words Tendency using Non_linear Approach

Author

Listed:
  • Talal H. Noor
  • El-Sayed Atlam
  • Ghada Elmarhomy
  • Ahmed Abd Elwahab
  • Rawda Draz
  • Mahmoud Elmarhoumy

Abstract

Field association (FA) terms are used to identify the subject of text (document field) by extracting specific words in that text. In this paper we use FA terms to study the effect of time change on specific terms by calculating the frequency of this terms, which associated with the archive field in a specific period. This paper also introduces a new approach for automatic evaluation of the stabilization classes using non-linear approach. The stabilization classes refer to the changing of FA terms with time in a specific period. The new approach improves the performance of decision tree than linear approach by using non-linear approach. The corpus that used in this approach has number of 1,356 files, and it is about 7.49 MB, after comparing the presented approach with the traditional one, we conclusion that the new approach enhanced the F-measure for increment, steady, decrement classes by 7.7%, 3.1%, 2.2%, sequentially.

Suggested Citation

  • Talal H. Noor & El-Sayed Atlam & Ghada Elmarhomy & Ahmed Abd Elwahab & Rawda Draz & Mahmoud Elmarhoumy, 2020. "Improvements of Automatic Extraction of FA Words Tendency using Non_linear Approach," Computer and Information Science, Canadian Center of Science and Education, vol. 13(3), pages 1-66, August.
    • Handle: RePEc:ibn:cisjnl:v:13:y:2020:i:3:p:66
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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