Utilizing Machine Learning for Precise Audience Targeting in Data Science and Targeted Advertising
Huan Ji, Xiaonan Xu, Guangze Su, Jiufan Wang, Yufu Wang
Abstract
In the current era of technology, big data has become increasingly accurate in understanding individuals' interests and needs. Personalized advertising recommendations have become a reality through the use of deep learning and intelligent algorithms. Whether it is a shopping app suggesting your favorite style of clothes or receiving relevant news feeds after discussing hot pot with friends, these are not coincidences but the result of machine learning. Machine learning has revolutionized advertising by providing outstanding performance. It has replaced the traditional approach that relied on the experience and intuition of practitioners. Powerful data processing and analysis capabilities are used to extract potential associations and patterns from massive amounts of data, providing new possibilities for advertisers and marketers. This includes applications such as idea generation, recommendation optimization, and bid strategy optimization, which have injected new vitality into the industry. The use of machine learning in data science and targeted advertising has yielded impressive results, offering users and advertisers more precise targeting and engaging advertising experiences. This field holds great promise and potential, and will undoubtedly continue to shape the future of the advertising industry.