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User behavior data based interest recommending method and device

An interest recommendation and interest technology, applied in the field of computer networks, can solve the problems of low user recognition, less data, and inaccurate user interest characteristics.

Active Publication Date: 2014-10-15
TENCENT TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the way that users actively mark often requires users to perform additional operations, the user recognition is not high, and the data that can be obtained is very small; the method of simply calculating the weight value of user interest based on the number of browsing times does not take into account the user's browsing times. The attenuation of user interests over time, so the obtained user interest characteristics are not accurate enough

Method used

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  • User behavior data based interest recommending method and device
  • User behavior data based interest recommending method and device
  • User behavior data based interest recommending method and device

Examples

Experimental program
Comparison scheme
Effect test

no. 1 example

[0018] refer to figure 1 , figure 1 It is a flowchart of an interest recommendation method based on user behavior data provided by the first embodiment of the present invention. In this embodiment, the interest recommendation method based on user behavior data includes:

[0019] Step S11: presetting a set of interest categories including multiple interest categories, and a time decay factor corresponding to each unit time period in k consecutive unit time periods, wherein k is a natural number;

[0020] Step S12: Obtain the first interest weight value of the designated user for each interest category in each unit time period according to the behavior data of the designated user in k consecutive unit time periods;

[0021] Step S13: Attenuate the first interest weight value of each interest category by the designated user in each unit time period according to the corresponding time decay factor, and obtain the designated user's interest in each interest category in the k cons...

no. 2 example

[0025] refer to figure 2 , figure 2 It is a flowchart of a method for recommending interests based on user behavior data provided by the second embodiment of the present invention. In this embodiment, the interest recommendation method based on user behavior data includes:

[0026] Step S21 , preset an interest category set including multiple interest categories, and a time decay factor corresponding to each unit time period in k consecutive unit time periods, wherein k is a natural number.

[0027] In this step, an interest category set (or called an interest category system) is firstly set, and the interest category set includes multiple interest categories. The various interest categories may have multiple hierarchical structures, for example, the interest category hierarchy shown in Table 1.

[0028] Table I

[0029] primary interest

secondary interest

Fiction

Time travel, romance, city...

games

Leisure, stand-alone, online games......

no. 3 example

[0046] refer to image 3 , image 3 It is a flowchart of an interest recommendation method based on user behavior data provided by the third embodiment of the present invention. In this embodiment, the interest recommendation method based on user behavior data includes:

[0047] Step S31 , preset an interest category set including multiple interest categories, and a time decay factor corresponding to each unit time period in k consecutive unit time periods, wherein k is a natural number.

[0048] For details of this step, reference may be made to the corresponding steps in the first embodiment, which will not be repeated here.

[0049] Step S32, obtain the behavior data of the designated user in k consecutive unit time periods, and obtain the page views A of each interest category by the designated user in each unit time period according to the behavior data of the designated user pv And the total number of browses of these interest categories by the specified user in each ...

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Abstract

The invention provides a user behavior data based interest recommending method and device. The method comprises the steps: pre-setting an interest category set, which comprises a variety of interest categories, and time attenuation factors, which respectively correspond to each of k continuous unit time periods, wherein k is a natural number; acquiring a first interest weight to each interest category of an appointed user in each unit time period according to behavior data of the appointed user in the k continuous unit time periods; attenuating the first interest weight to each interest category of the appointed user in each unit time period according to a time attenuation factor corresponding to the first interest weight, so as to obtain an interest feature weight to each interest category of the appointed user in the k continuous unit time periods; carrying out interest recommending on the appointed user according to the interest feature weight of each interest category. According to the method and the device, the accuracy of user interest features can be effectively improved.

Description

technical field [0001] The invention relates to the technical field of computer networks, in particular to a method and device for recommending interests based on user behavior data. Background technique [0002] With the rapid development of computer technology and network technology, network information has grown explosively. On the one hand, it meets the needs of users for information volume, and on the other hand, it also produces some problems, such as scattered resources and centralized retrieval. are all the same. For ordinary users, "information trek" and "information overload" have become increasingly serious problems. The key to solving these problems is to transform the network from passively accepting users' requests to actively sensing users' information needs, so as to realize personalized active information services for users. [0003] In order to realize personalized active information service, it is first necessary to understand the user's interest, and de...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 程小梅苏小康曾鹏云范世青
Owner TENCENT TECH (SHENZHEN) CO LTD
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