Web robots are applications which recursively and automatically overview the content of website documents. Some robots
are considered to be malicious. Hence, identifying web robots is a classification challenge. In this research we mainly present a hybrid
particle swarm optimization method and fuzzy system aiming at increasing efficiency over Web robot detection and simulation by
MATLAB software. Evaluation criteria are considered: Specificity, Accuracy, F- Measure, Recall and Precision. Results of the study for
the proposed method are respectively: 99.81, 96.92, 96.10, 91.39 and 99.58. The yields for proposed basic fuzzy system and fuzzy
network algorithm and ANFIS neural fuzzy network algorithm indicate the priority of the proposed method other than algorithms being
compared.
Published In:IJCSN Journal Volume 7, Issue 4
Date of Publication : August 2018
Pages : 272-278
Figures :07
Tables : 03
Mohammad Ordouei :
Computer Engineering Dep., Islamic Azad University (IAU)
Tehran,Iran
Iman Namdar :
Computer Engineering Dep., Islamic Azad University (IAU)
Tehran,Iran
Web robot detection; fuzzy system; particle swarm optimization algorithm
This paper aimed at providing a hybrid method to improve
web robots accuracy. Of the features of proposed method
than similar works we consider:
- Providing a novel method to detect Web robots
influence
- Improve efficiency detecting web robots
The paper investigated through MATLAB software, the
results were compared using algorithms. To test the
performance of the proposed method some criteria
including Precision, Accuracy, F-Measure, Recall and
Specificity were considered. Conducting experiments
yielded that the proposed algorithm was better than the
other ones.
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