Reviewing the websites of Tehran Municipality and providing appropriate data mining solutions

Subject Areas : Journal of Knowledge Studies

shaysteh shojaei karizaki ¹ (PhD Student, Department of Knowledge& Information Science, Information Retrieval Orientation, Tonekabon Branch, Islamic Azad University, Iran)
sudabeh Shapoori ² (Assistant Professor, Department of Knowledge &Information Science, Tonekabon Branch, Islamic Azad University, Iran.)
hajar zarei ³ (Assistant Professor, Department of Knowledge &Information Science, Tonekabon Branch, Islamic Azad University, Iran.)

Received: 2020-08-19 Accepted : 2020-09-24 Published : 2019-10-23

Keywords: Data mining, Neural network, Decision tree, Tehran Municipality, Website Review,

Abstract :

Objective: The main purpose of this study is to identify and analyze different types of data on the website of Tehran Municipality and to provide appropriate data mining solutions. Method: This research is fundamental and in terms of nature it can be considered analytical. The data collection method was field and the statistical population of 47 sites were selected among 220 domains of Tehran Municipality and data mining techniques were used for analysis and the source of data collection is web analytics and tools used by Google Analytics. Results: The accuracy of the normal neural network algorithm is equal to 99.25% and the RMS standard of the normal neural network algorithm is equal to 0.159. The accuracy of the decision tree algorithm is 99.80% and the MSI criterion of the decision tree algorithm is 0.003 and finally the RMS criterion of the decision tree algorithm is 0.045. The accuracy of the CNN algorithm is equal to 99.81% and finally the RMS criterion of the CNN algorithm is equal to 0.035. Conclusion: Based on the obtained findings, the DB Scan method is equal to other basic methods for analyzing data of Tehran Municipality websites and has a higher accuracy than other methods.

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