Article recommendation method and device
A recommendation method and item technology, applied in the computer field, can solve the problems of cold start of new items, poor recommendation effect, and low recommendation accuracy, and achieve the effect of improving the accuracy.
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Embodiment 1
[0020] figure 1 The implementation process of the item recommendation method provided by Embodiment 1 of the present invention is shown. For the convenience of description, only the parts related to the embodiment of the present invention are shown, and the details are as follows:
[0021] In step S101 , according to the similarity between the rated item and the item to be rated in the historical scoring data, the influence factor of the predicted rating of the item to be rated in the historical scoring data is calculated.
[0022] In the embodiment of the present invention, according to the pre-obtained similarity between the user's rated items and the items to be rated, the influence factor of the predicted rating of the rated items in the historical rating data to the items to be rated is calculated.
[0023] Preferably, before calculating the impact factor of the predicted rating of the rated item in the historical rating data, the item to be rated and the text content of ...
Embodiment 2
[0037] figure 2 The structure of the item recommendation device provided by the second embodiment of the present invention is shown. For the convenience of description, only the parts related to the embodiment of the present invention are shown, including:
[0038] The factor calculation unit 21 is used to calculate the influence factor of the predicted score of the item to be rated based on the historical rating data according to the similarity between the rated item and the item to be rated in the historical rating data.
[0039] In the embodiment of the present invention, the factor calculation unit calculates the influence factor of the predicted rating of the rated item in the historical scoring data according to the similarity between the user's rated item and the item to be rated in advance.
[0040] Preferably, before calculating the impact factor of the predicted rating of the rated item in the historical rating data, the item to be rated and the text content of the ...
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