Method and system of recommending application resources
A resource and a technology of various applications, applied in transmission systems, electrical components, program control devices, etc., can solve problems such as poor results and low efficiency, and achieve the effect of improving the recommendation effect
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Embodiment 1
[0022] User groups can be divided into game groups, weather groups, shopping groups, communication groups, social groups, etc. The game group is a user group interested in game applications, the weather group is a group interested in weather applications, the shopping group is a group interested in shopping applications, and the communication group is interested in instant messaging tools or communication applications The social group is a group interested in various dating apps. Of course, the grouping of users is not limited to this, and users can be grouped into more groups, such as hotel reservation groups, air ticket or train ticket reservation groups, map or navigation groups, etc. The type of grouping can be dynamically adjusted, and the above examples are not intended Restricting the division of user groups.
[0023] The historical records of users other than typical users may not be able to directly reflect the significance of a certain user group from the proportion...
Embodiment 2
[0047] The historical record acquisition module 201 collects historical records during the use of applications by each user; the historical records include the types of applications used and at least one data in other dimensions; the applications are installed in smart TV devices;
[0048] A typical user selects the division module 202, collects statistics on the collected historical records of each user, calculates the proportion of each type of application according to the number of applications used by each user, and classifies the user into a group whose proportion is greater than the threshold A user group corresponding to a specific type of application, the user is defined as a typical user, and a user group including typical users corresponding to each specific type of application is generated;
[0049] The model training module 203 obtains the data characteristics of typical users in other dimensions in each user group respectively, and determines the group characterist...
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