Health intervention scheme personalized recommendation method and system based on time sequence early warning signal
A health intervention and program technology, applied in the field of health care, can solve problems such as inaccurate results, lack of dynamic recommendation programs, and does not consider the individual physical characteristics of patients, so as to achieve the effect of improving accuracy
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Embodiment 1
[0062] In the first aspect, the present invention first proposes a personalized recommendation method for health intervention schemes based on time series early warning signals, see figure 1 , the method includes:
[0063] S1. Obtain user health data and preprocess the user health data;
[0064] S2. Based on the preprocessed user health data, obtain a user item rating matrix and a preference matrix of Tag label attributes;
[0065] S3. Based on the user-item scoring matrix and the preference matrix of Tag label attributes, use the SVD collaborative filtering algorithm to obtain a preliminary recommendation scheme set;
[0066] S4. Using the BP-DS neural network to locally adjust the set of preliminary recommendation schemes to obtain a complete recommendation scheme;
[0067] S5. Dynamically update the complete recommendation scheme based on the sequential update data generated by executing the complete recommendation scheme.
[0068] It can be seen that the technical solut...
Embodiment 2
[0200] In the second aspect, the present invention also discloses a personalized recommendation system for health intervention programs based on time series early warning signals, the system includes:
[0201] A data acquisition and preprocessing module, configured to acquire user health data and preprocess the user health data;
[0202] A data reprocessing module, configured to obtain a user-item rating matrix and a preference matrix for Tag label attributes based on the preprocessed user health data;
[0203] A preliminary recommendation scheme generation module is used to obtain a preliminary recommendation scheme set based on the user item rating matrix and the preference matrix of the Tag label attribute, using the collaborative filtering algorithm of SVD
[0204] A complete recommendation scheme generating module, configured to use the BP-DS neural network to locally adjust the set of preliminary recommendation schemes to obtain a complete recommendation scheme.
[0205...
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