A New Approach of Time Series Variation Based on Power Links and Field Association Words

Autor:	Zohair Malki, El-Sayed Atlam, Talal H. Noor, Abdallah A. Mohamed, Ghada Elmarhomy, Ahmad Reda Alzighaibi
Rok vydání:	2020
Předmět:	Series (mathematics) Association (object-oriented programming) Statistics Decision tree Variation (game tree) Stability (probability) Field (computer science) Mathematics Power (physics) Link analysis
Zdroj:	Journal of Computer and Communications. :72-85
ISSN:	2327-5227 2327-5219
DOI:	10.4236/jcc.2020.83008
Popis:	This paper has proposed a new methodology extracting stability classes of field association words depending on automatically power link analysis to enhance the precision of decision tree. In this paper, we have studied the effects of the time variation based on the frequencies of specific words called field association words that connected to documents using power link in a specific period. The stability classes have referred to the popularity of field association words based on the change of time in a given period. The new approach has evaluated by conducting experiments simulating results of 1575 files (about 5.16 MB). Based on these experiments, it has turned out that, the F-measure for ascending, stable and descending classes have achieved 93.6%, 99.8% and 75.7%, respectively. These results mean that F-measure was increasing by 12%, 4% and 34% than traditional methods because of the power link analysis.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c06cc9ffb90bb25caecc21478549e834 https://doi.org/10.4236/jcc.2020.83008 Zobrazit plný text záznamu