Item recommending method and device
A recommendation method and item technology, applied in the computer field, can solve the problems of large recommendation limitations and inability to be recommended by users, and achieve the effect of reducing limitations
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Embodiment 1
[0082] figure 1 It is a flow chart of the steps of an item recommendation method provided in Embodiment 1 of the present invention, as shown in figure 1 As shown, the method may include:
[0083] Step 101: Determine the target user's preference value for each topic according to the preference value of each user in the network system for the topic that has been interacted with.
[0084] In the actual application scenario, each user has interacted topics and topics that have not been interacted with. In the embodiment of the present invention, when recommending items to the target user, it can be determined by each user's preference value for the interacted topic Find the target user's preference value for each topic, that is, determine the target user's preference value for the interactive topic and the preference value for the uninteracted topic. Wherein, the preference value may be determined according to the historical interaction data between each user and the interacted ...
Embodiment 2
[0095] figure 2 It is a flow chart of the steps of an item recommendation method provided in Embodiment 2 of the present invention, such as figure 2 As shown, the method may include:
[0096] Step 201. According to the historical interaction data of each user in the network system, calculate each user's preference value for each interacted item.
[0097] Taking the network system as the video system, the items as videos, and the historical interaction data including the videos clicked by the user and the viewing time corresponding to each video as an example, each user is regarded as the user to be calculated, and the following steps 2011 to 2013 are performed respectively, To realize the calculation of each user's preference value for each interacted item. As an example, assume that the video system includes three users: user a, user b and user c. In this step, user a, user b and user c can be respectively used as users to be calculated, and then user a, user b and user c...
Embodiment 3
[0160] image 3 is a block diagram of an item recommendation device provided in Embodiment 3 of the present invention, such as image 3 As shown, the device 30 may include:
[0161] The first determination module 301 is configured to determine the target user's preference value for each topic according to the preference value of each user in the network system for the topic that has been interacted with;
[0162] The second determination module 302 is configured to determine the target user's preference value for each item to be recommended according to the topic to which each item to be recommended belongs and the target user's preference value for each topic;
[0163] The recommendation module 303 is configured to recommend to the target user items to be recommended whose preference value is greater than a preset threshold.
[0164] To sum up, in the item recommendation device provided by Embodiment 3 of the present invention, the first determination module can determine t...
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