A method and system for implementing information recommendation
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A technology of information recommendation and recommendation list, applied in the field of information processing, can solve the problems of single recommendation information and few consideration factors
Active Publication Date: 2017-12-19
TCL CORPORATION
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[0003] In order to solve the problem of few considerations and single recommendation information in the recommendation system in the prior art, the embodiment of the present invention provides a method and system for implementing information recommendation
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Embodiment 1
[0024] Embodiment 1 of the present invention provides a method for implementing information recommendation, such as figure 1 As shown, the method includes:
[0025] Step S10: When receiving the recommendation request sent by the client, generate a related recommendation list according to the information that the user is currently browsing and the information similarity model. Wherein, the information similarity model is an information similarity matrix calculated offline by the background service according to the information browsed by the user at a preset period.
[0026] In this embodiment, the client can send a recommendation request to the server through the API interface function. The information currently browsed by the user may be videos, pictures, commodities, music, etc. browsed by the user at a certain location at the current time.
[0027] In this embodiment, the background service in the server performs offline calculation on the information browsed by the user a...
Embodiment 2
[0064] Embodiment 2 of the present invention provides a system for implementing information recommendation, the system is set on a server, such as image 3 As shown, the system includes:
[0065] The first recommendation list generation module 100 is configured to generate a related recommendation list according to the information that the user is currently browsing and the information similarity model when receiving the recommendation request sent by the client,
[0066] Wherein, the information similarity model is an information similarity matrix calculated offline by the background service according to the information browsed by the user at a preset period.
[0067] The second recommendation list generation module 200 is used to generate a non-personalized recommendation list according to the behavioral data statistical model,
[0068] Among them, the behavior data statistical model is the behavior data that the background service calculates offline according to the user's...
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Abstract
The invention discloses a method and system for recommending information. The method includes the steps that when a recommending request sent by a client is received, a relevant recommending list is generated according to current information browsed by a user and an information similarity model; a non-personalized recommending list is generated according to a statistic model of behavior data; a personalized recommending list is generated according to the information similarity model, the statistic model of the behavior data and a user interest model; a comprehensive recommending list is generated according to the generated relevant recommending list, the generated personalized recommending list and the non-personalized recommending list; the generated comprehensive recommending list is returned to the client as the recommending result. With the method and system, a result meeting the interest of the user and the information scene currently browsed by the user can be recommended to the user, and the method and system can meet user requirements better by adjusting the recommending result according to a recommending strategy.
Description
technical field [0001] The invention relates to the field of information processing, in particular to a method and system for implementing information recommendation. Background technique [0002] With the development of information technology and the Internet, people have gradually entered an era of information overload from an era of information scarcity. As we all know, in order to solve the problem of information overload, countless scientists and engineers have proposed many genius solutions, among which the representative solutions are catalogs and search engines. Search engines allow users to find the information they need by searching keywords. However, search engines require users to actively provide accurate keywords to find information, so they cannot solve many other needs of users. For example, when users cannot find keywords that accurately describe their needs, search engines are helpless. Like search engines, recommendation systems have always been a way to...
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