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A new retrieval method based on time series variation using field association terms
Author(s) -
Atlam ElSayed,
Ghaleb Fayed,
Taha Azaa,
Ismail Aya
Publication year - 2018
Publication title -
mathematical methods in the applied sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.719
H-Index - 65
eISSN - 1099-1476
pISSN - 0170-4214
DOI - 10.1002/mma.4713
Subject(s) - mathematics , field (mathematics) , series (stratigraphy) , tree (set theory) , measure (data warehouse) , point (geometry) , association (psychology) , decision tree , algorithm , statistics , variation (astronomy) , data mining , computer science , combinatorics , pure mathematics , geometry , paleontology , philosophy , epistemology , biology , physics , astrophysics
This paper studies the effects of the time change on the frequencies of specific terms connected to the document field in a given period. These specific terms are the field association (FA) terms. The paper also suggests a new method for automatic evaluation of the stabilization classes of FA terms to improve the precision of decision tree. The stabilization classes point out the popularity of list of FA terms depending on time change. Moreover, the suggested method manipulates the problem of the scattering of data numbers among classes to improve the performance of decision tree precision. The presented method is evaluated through conducting experiments by simulating the result of 1245 files, which are equivalent to 4.15 MB. The F‐measure for increment, fairly steady, and decrement classes achieves %90.4, %99.3, and %38.6, sequentially.