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2020 | OriginalPaper | Chapter

Empirical Study of Soft Clustering Technique for Determining Click Through Rate in Online Advertising

Authors : Akshi Kumar, Anand Nayyar, Shubhangi Upasani, Arushi Arora

Published in: Data Management, Analytics and Innovation

Publisher: Springer Singapore

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Abstract

Online advertising is an industry with the potential for maximum revenue extraction. Displaying the ad which is more likely to be clicked plays a crucial role in generating maximum revenue. A high click through rate (CTR) is an indication that the user finds the ad useful and relevant. For suitable placement of ads online and rich user experience, determining CTR has become imperative. Accurate estimation of CTR helps in placement of advertisements in relevant locations which would result in more profits and return of investment for the advertisers and publishers. This paper presents the application of a soft clustering method namely fuzzy c-means (FCM) clustering for determining if a particular ad would be clicked by the user or not. This is done by classifying the ads in the dataset into broad clusters depending on whether they were actually clicked or not. This way the kind of advertisements that the user is interested in can be found out and subsequently more advertisements of the same kind can be recommended to him, thereby increasing the CTR of the displayed ads. Experimental results show that FCM outperforms k-means clustering (KMC) in determining CTR.

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Literature
1.
go back to reference Avila Clemenshia, P., Vijaya, M.S.: Click through rate prediction for display advertisement. Int. J. Comput. Appl. 975, 8887 (2016) Avila Clemenshia, P., Vijaya, M.S.: Click through rate prediction for display advertisement. Int. J. Comput. Appl. 975, 8887 (2016)
2.
go back to reference Graepel, T., Candela, J., Borchert, T., Herbrich, R.: Web-scale bayesian click-through rate prediction for sponsored search advertising in microsoft’s bing search engine. In: IJCA (2010) Graepel, T., Candela, J., Borchert, T., Herbrich, R.: Web-scale bayesian click-through rate prediction for sponsored search advertising in microsoft’s bing search engine. In: IJCA (2010)
3.
go back to reference Hillard, D., Schroedl, S., Manavoglu, E., Raghavan, H., Leggetter, C.: Im-proving ad relevance in sponsored search. In: ACM (2010) Hillard, D., Schroedl, S., Manavoglu, E., Raghavan, H., Leggetter, C.: Im-proving ad relevance in sponsored search. In: ACM (2010)
4.
go back to reference Kondakindi, G., Rana, S., Rajkumar, A., Ponnekanti, S.K., Parakh, V.: A logistic regression approach to ad click prediction (2014) Kondakindi, G., Rana, S., Rajkumar, A., Ponnekanti, S.K., Parakh, V.: A logistic regression approach to ad click prediction (2014)
5.
go back to reference Shi, L., Li, B.: Predict the click through rate and average cost per click for key-words using machine learning methodologies. In: IEOM (2016) Shi, L., Li, B.: Predict the click through rate and average cost per click for key-words using machine learning methodologies. In: IEOM (2016)
6.
go back to reference Wang., C.J., Chen, H.H.: Learning user behaviors for advertisements click predictions. In: ACM (2011) Wang., C.J., Chen, H.H.: Learning user behaviors for advertisements click predictions. In: ACM (2011)
7.
go back to reference Chakrabarti, D., Agarwal, D., Josifovski, V.: Contextual advertising by combining relevance with click feedback. In: WWW (2008) Chakrabarti, D., Agarwal, D., Josifovski, V.: Contextual advertising by combining relevance with click feedback. In: WWW (2008)
8.
go back to reference Cheng, H., Cantú-Paz, E.: Personalized click prediction in sponsored search. In: ACM (2010) Cheng, H., Cantú-Paz, E.: Personalized click prediction in sponsored search. In: ACM (2010)
9.
go back to reference Edizel, B., Mantrach, A., Bai, X.: Deep character-level click-through rate prediction for sponsored search. In: Stat.ml (2017) Edizel, B., Mantrach, A., Bai, X.: Deep character-level click-through rate prediction for sponsored search. In: Stat.ml (2017)
10.
go back to reference Yadav, J., Sharma, M.: A review of K means algorithm. Int. J. Eng. Trends Technol. 4(7), 2972–2976 (2013) Yadav, J., Sharma, M.: A review of K means algorithm. Int. J. Eng. Trends Technol. 4(7), 2972–2976 (2013)
11.
go back to reference Yanyun, C., Jianlin, Q., Xiang, G., Jianping, C., Dan, J., Li, C.: Advances in research of fuzzy c means algorithm. In: International Conference on Network Computing and Information Security (2011) Yanyun, C., Jianlin, Q., Xiang, G., Jianping, C., Dan, J., Li, C.: Advances in research of fuzzy c means algorithm. In: International Conference on Network Computing and Information Security (2011)
12.
go back to reference Bhatia, M.P.S., Kumar, A.: Information retrieval and machine learning: supporting technologies for web mining research and practice. Webology 5(2), 5 (2008) Bhatia, M.P.S., Kumar, A.: Information retrieval and machine learning: supporting technologies for web mining research and practice. Webology 5(2), 5 (2008)
Metadata
Title
Empirical Study of Soft Clustering Technique for Determining Click Through Rate in Online Advertising
Authors
Akshi Kumar
Anand Nayyar
Shubhangi Upasani
Arushi Arora
Copyright Year
2020
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-32-9949-8_1