Prediction Algorithm for Optimal Ranking of Search Keyword by TensorFlow 


Vol. 43,  No. 8, pp. 1347-1356, Aug.  2018
10.7840/kics.2018.43.8.1347


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  Abstract

Although the value of the search keyword is generally calculated based on the frequency of the search word, the search engine configures the price of the search keyword to be bid through the blind auction method without disclosing the price in real time. As a result, it is difficult to reach a desired optimal ranking by selecting a price with a statistical method that is passive in order to predict the price of the search keyword. In this paper, we propose a modeling algorithm to predict the optimal ranking of search keywords by collecting search keywords from the largest search engine in Korea. In particular, we propose a mechanism for constructing an automated ranking prediction system for a search keyword by comparing and analyzing the prediction accuracy whether the optimal ranking is reached for each algorithm by applying a machine learning algorithm.

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  Cite this article

[IEEE Style]

M. Ji and H. Park, "Prediction Algorithm for Optimal Ranking of Search Keyword by TensorFlow," The Journal of Korean Institute of Communications and Information Sciences, vol. 43, no. 8, pp. 1347-1356, 2018. DOI: 10.7840/kics.2018.43.8.1347.

[ACM Style]

Minjun Ji and Hyunhee Park. 2018. Prediction Algorithm for Optimal Ranking of Search Keyword by TensorFlow. The Journal of Korean Institute of Communications and Information Sciences, 43, 8, (2018), 1347-1356. DOI: 10.7840/kics.2018.43.8.1347.

[KICS Style]

Minjun Ji and Hyunhee Park, "Prediction Algorithm for Optimal Ranking of Search Keyword by TensorFlow," The Journal of Korean Institute of Communications and Information Sciences, vol. 43, no. 8, pp. 1347-1356, 8. 2018. (https://doi.org/10.7840/kics.2018.43.8.1347)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880