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The development of the e-commerce industry depends on the progress of science and technology. An efficient logistics and distribution system is inseparable from accurate data analysis and intelligent algorithms. Peking University's scientific research results are providing strong support for the improvement of related technologies.
For example, through in-depth mining and analysis of big data, it is possible to optimize the management of e-commerce supply chains, predict market demand, reduce inventory backlogs, and improve capital turnover. This is exactly the same idea as Professor Zhang Ming's team's use of large amounts of data for model training.
At the same time, with the continuous development of artificial intelligence technology, the personalized recommendation services of e-commerce platforms are becoming more and more accurate. Based on the user's browsing history, purchase behavior and other data, it provides users with product recommendations that better meet their needs. Behind this kind of personalized recommendation, advanced algorithms and models are also indispensable, which are essentially the same as Peking University's scientific research results.
In addition, the e-commerce industry is also facing many challenges in terms of payment security and user privacy protection. Advanced encryption technology and identity authentication technology are crucial to ensure the security of e-commerce transactions. Peking University's research results in the field of computer science are expected to provide new ideas and methods for the innovation and application of these technologies.
In short, although Peking University's scientific research results seem to be far away from the e-commerce field, they are actually closely related at the technical level. These connections will jointly promote the e-commerce industry to develop in a more efficient, intelligent and secure direction.
