The implementation of an AI-driven advertising push system based on a NLP algorithm

Qi Xin; Yuhang He; Yiming Pan; Yong Wang; Shuqian Du

doi:10.62051/ijcsit.v1n1.05

Authors

Qi Xin
Yuhang He
Yiming Pan
Yong Wang
Shuqian Du

DOI:

https://doi.org/10.62051/ijcsit.v1n1.05

Keywords:

Intelligent recommendation, NLP algorithm, Data mining, Artificial intelligence

Abstract

The advertising industry is developing very rapidly, especially outdoor advertising, which has attracted people's attention. All kinds of commercial advertisements can be seen everywhere in outdoor public places, but the advertising delivery system on the market is relatively simple in function, and the evaluation of advertising effect lacks effective automatic analysis means, mainly carried out by manual observation, which is low in efficiency and difficult to conduct quantitative evaluation, which directly leads to the lack of targeted advertising. Artificial intelligence advertising refers to the use of artificial intelligence technology (such as voice recognition, face recognition, deep learning, machine learning, etc.), investigation, production, publishing advertising and other fields, the combination of artificial intelligence and advertising brings great value and convenience to people's lives. Among them, the most common algorithm that can achieve accurate and intelligent advertising is NLP, and the artificial intelligence advertising push system based on natural language processing (NLP) algorithm can provide a variety of useful applications in the advertising field. These applications can help advertisers better understand user needs, improve the accuracy and effectiveness of ads, and provide a better user experience. In order to fully tap the advertising information value contained in unstructured data, this paper introduces the text mining technology based on natural language processing, explores from principle to practice, and analyzes the push process and application of intelligent advertisements in daily life by analyzing the implementation steps of NLP algorithm model.

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