Research Trends on the Usage of Machine Learning and Artificial Intelligence in Advertising

被引:0
作者
Neil Shah
Sarth Engineer
Nandish Bhagat
Hirwa Chauhan
Manan Shah
机构
[1] SAL Institute of Technology and Engineering Research,Department of Computer Engineering
[2] Pandit Deendayal Petroleum University,Department of Chemical Engineering, School of Technology
关键词
Artificial intelligence; Machine learning; Advertising;
D O I
10.1007/s41133-020-00038-8
中图分类号
学科分类号
摘要
Advertising is a way in which a company introduces possible customers to a company’s product/service, the main objective is possibly to convince them to buy their product or use their service. The significance of Advertising is critical for the company, as this alone can make people aware of the company’s product and in doing so can generate a good possibility of it being sold to the customers. It is inevitable for companies to face changes and one such change is the evolution in the way of doing Advertisement. Advertisement is now done with the help of not so newfound helping hand that is Artificial Intelligence and Machine Learning. The answer to the question as to why the change in the process of Advertising is important lies in the before-after statistical observations of companies using this technology. The results themselves are reasonable motivating factors for companies who are yet to acknowledge the change. The serious challenge to this new version of Advertising is to make sure to not allow the usage of it to such a great extent where ordinary person is concerned about his/her privacy. Implementing Advertisements this way, we are quite sure that making laws, enforcing the laws or even having its own governing body can ensure righteous use of deploying this technology. The future of Advertising is going to be even better than before as Artificial Intelligence and Machine Learning will bring more control of Advertising to companies. Summing up, we feel confident that Advertising with Artificial Intelligence and Machine Learning are here for a noticeable and a significant change.
引用
收藏
相关论文
共 190 条
  • [21] Shah M(2018)Artificial intelligence in advertising J Advert Res 95 103-8
  • [22] Ahir K(2014)Machine learning for targeted display advertising: transfer learning in action Mach Learn 14 3207-11
  • [23] Govani K(2013)Counterfactual reasoning and learning systems: the example of computational advertising J Mach Learn Res 2 55-519
  • [24] Gajera R(2020)Machine learning in films: an approach towards automation in film censoring J Data Inf Manag 5 5-81
  • [25] Shah M(2020)Fatigue detection using artificial intelligence framework Augment Hum Res 5 10-389
  • [26] Evans DS(2020)Preprocessing of non-symmetrical images for edge detection Augment Hum Res 16 15-13
  • [27] Talaviya T(2014)CAVVA: Computational affective video-in-video advertising IEEE Trans Multimedia 3 21-55
  • [28] Shah D(2020)A comprehensive study on critical security issues and challenges of the IoT world J Data Inf Manag 5 12-658
  • [29] Patel N(2020)Systematic review and meta-analysis of augmented reality in medicine, retail, and games Vis Comput Ind Biomed Art 7 1-28
  • [30] Yagnik H(2020)A comparative analysis of logistic regression, random forest and KNN models for the text classification Augment Hum Res 18 999-432