Method and device for game community recommendation
A game and community technology, applied in the field of communication, can solve the problem of low success rate of users to be recommended
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Embodiment 1
[0057] figure 1 It is a flow chart of Embodiment 1 of a method recommended by a game community in the present invention. The method includes:
[0058] Step 101: Preset game community recommendation rules.
[0059] After the game user logs in the game software, in order to better communicate with other game users who have registered the game software, the game user will apply to join the game community of the game software. When a game user requests to join a game community, if the administrator of the game community accepts the request of the game user, the game user successfully joins the game community; if the administrator of the game community rejects the request of the game user, the game User failed to join the game community.
[0060] When setting the game community recommendation rules, first obtain a large number of training samples, which include a large number of game users and game communities. The event that a game user successfully joins a game community in the...
Embodiment 2
[0085] figure 2 It is a flow chart of Embodiment 2 of a method recommended by a game community in the present invention. Compared with Embodiment 1, Embodiment 2 uses user attributes and community attributes to pre-set game community recommendation rules. The method includes:
[0086] Step 201: Obtain multiple positive samples and multiple negative samples.
[0087] As described in Embodiment 1, a large number of training samples are established, including a large number of game users and game communities, and the event that a game user successfully joins a game community in the training sample is regarded as a positive sample, and the event that a game user does not join is regarded as a positive sample. Events in the game community are regarded as a negative sample.
[0088] Step 202: Extract the user attributes of game users in each positive sample as successful user attributes, extract the community attributes of game communities in each positive sample as successful com...
Embodiment 3
[0154] image 3 It is a flow chart of Embodiment 3 of a game community recommendation method of the present invention. Compared with Embodiment 1, Embodiment 3 uses user attributes, community attributes, and analysis attributes to pre-set game community recommendation rules. The method includes:
[0155] Step 301: Obtain multiple positive samples and multiple negative samples.
[0156] Step 302: Extract the user attributes of the game users in each positive sample as successful user attributes, extract the community attributes of the game community in each positive sample as successful community attributes, and extract the user attributes of game users in each negative sample as Failed user attributes, extracting the community attributes of the game community in each negative sample as failed community attributes.
[0157] Step 301 is similar to step 201 in the second embodiment, step 302 is similar to the step 202 in the second embodiment, refer to the description of the sec...
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