The Digital Advertising has emerged as one of the main source of revenue for major part of Internet economy. The audience communicates with the digital world by using search engines, social networking, online market-ing and banking sites and many more. To generate more income through advertisement the ad-publishers and the ad-networks need to be watchful about users interest when targeting them for their brand or product pro-motion through these channels. The placement of advertisement depends on the users interest is as it involves the higher probability of a click on the ad, which offers benefit to all the entities, involved. This paper surveys different clustering approaches proposed by various authors for user clustering. At the end of the paper, the various methods are compared based on phases, techniques and usages.
CITATION STYLE
Vachharajani, H., Gupta, R. K., & Pathik, N. (2019). User clustering algorithms in online advertising. International Journal of Recent Technology and Engineering, 8(2 Special Issue 4), 29–35. https://doi.org/10.35940/ijrte.B1006.0782S419
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