Quantum computing auxiliary analysis and marketing prediction method for private domain flow pool data

Through quantum computing technology, the analysis and prediction of private domain traffic pool data is solved, and the problems of inaccurate data analysis, low search efficiency, slow calculation and insufficient security in the existing technology are solved, achieving more efficient and accurate marketing prediction and personalized marketing.

CN119648271AInactive Publication Date: 2025-03-18GUANGZHOU JINGCUI EDUCATION TECH CO LTD
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Patent Information

Application Number
CN202411710837.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-11-27
Publication Date
2025-03-18
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

The prior art has problems such as inaccuracy, low search efficiency, slow calculation and insufficient security in private domain traffic pool data analysis and marketing prediction.

Method used

Quantum computing technology is used to assist in the analysis of private domain traffic pool data, user behavior data is encoded through quantum algorithms, features are extracted using quantum support vector machines, periodic patterns are analyzed by quantum Fourier transform, marketing prediction models are constructed based on quantum algorithms, and model parameters are optimized using quantum annealing technology.

Benefits of technology

It improves the accuracy of marketing forecasts, improves search efficiency and computing power, enhances data security, and achieves better resource allocation and personalized marketing.

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Abstract

The invention provides a quantum computing auxiliary analysis and marketing prediction method for private domain traffic pool data, which comprises the following steps of: acquiring and processing user behavior data, coding the user behavior data into a quantum state by using a quantum algorithm, extracting user behavior characteristics by using a quantum support vector machine (QSVM), and analyzing a periodic mode through quantum Fourier transform, so as to realize the quantum computing auxiliary analysis and marketing prediction of the private domain traffic pool data. According to the method, a marketing prediction model is constructed based on a quantum algorithm, model parameters are optimized by using a quantum annealing technology, the prediction accuracy is improved, and the method further comprises the step of carrying out classical verification and optimization on a quantum calculation result so as to realize personalized marketing. According to the invention, efficient analysis and precise marketing prediction of the private domain traffic pool are realized, and the pertinence and effectiveness of enterprise marketing strategies are improved.
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