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Information pushing method and device
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An information push and probabilistic technology, applied in the field of communication, can solve the problems of biased recommended results, large limitations, and lack of diversity in results
Active Publication Date: 2016-10-05
CHINA MOBILE COMM GRP CO LTD
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[0009] The present invention provides a method for pushing information, which is used to solve the problems of lack of diversity in recommended results, deviations in recommended results, or large limitations when information is pushed based on a collaborative filtering recommendation method
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Embodiment 1
[0048] Embodiment 1 of the present invention proposes a method for pushing information, such as figure 1 As shown, the specific process is as follows:
[0049] Step 101, acquiring a user ID and activity history data of the user corresponding to the user ID.
[0050] The activity history data includes the activity scene and activity type in which the user participated in the activity.
[0051] A specific example is used to illustrate the technical solution proposed in Embodiment 1 of the present invention in detail.
[0052] The user ID is represented by u, the user ID is obtained, and all user IDs form a user set. The user set is denoted by U, as follows:
[0053] Step 1: User u i and other users together form the user set U={u 1 , u 2 ,...u i ,...u m}.
[0054] Step 2: Obtain the activity history data of each user.
[0055] First, determine the activity set and activity type. Specifically as follows:
[0056] A: The set of all activities is the set of activities, ...
Embodiment 2
[0157] The embodiment of the present invention proposes a device for pushing information, such as figure 2 As shown, the device includes:
[0158] The acquiring unit 201 is configured to acquire a user identifier and activity history data of the user corresponding to the user identifier, wherein the activity history data includes activity scenarios and activity types in which the user participates in activities.
[0159] The probability determination unit 202 is configured to determine a first probability and a second probability for any activity type according to the user corresponding to any user identifier according to the activity history data of the user, wherein the first probability is that the user does not The probability of activities that have participated in, the activities that have not participated in are included in the activity type; the second probability is the probability of activities that the user has participated in determined according to the user's fri...
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Abstract
The invention discloses an information pushing method and device. The information pushing method includes: acquiring a user identification and activity historical data of a user corresponding to the user identification, determining the first probability and the second probability according to the activity historical data of the user for one user corresponding to any one user identification; determining the third probability that the user takes part in different types of activities in different activity scenes; determining the fourth probability that the user takes part in a designated type of activity in any one activity scene according to the first probability, the second probability, and the third probability; and performing information pushing on the user according to the fourth probability. The information pushing method can solve the problem that a recommended result is poor in diversity, has errors, or is large in limitation during information pushing based on a collaborative filtering recommendation manner.
Description
technical field [0001] The present invention relates to the field of communication technologies, in particular to a method and device for pushing information. Background technique [0002] With the rapid development of the Internet, the content on the Internet is also showing explosive growth. In order to solve the problem of information overload for users when faced with massive content, recommendation technology has emerged as the times require. As one of the earliest and most successful recommendation techniques, collaborative filtering recommendation (English: Collaborative Filtering Recommendations, abbreviation: CFR) algorithm has been successfully applied to e-commerce systems. [0003] Usually, the user's activities can be mined based on the collaborative filtering recommendation algorithm, and then the corresponding information can be pushed to the user according to the mining results. Among them, activities refer to the sum of actions that are united by a common p...
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