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Content recommendation method and device, electronic device, and storage medium

A content recommendation and storage medium technology, applied in the Internet field, can solve problems such as unsatisfactory recommendation effects, and achieve the effect of ensuring timeliness

Inactive Publication Date: 2019-03-29
深圳墨世科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The information recommended by the platform to users is often determined by various algorithms, and the algorithms need to undergo a large amount of data training and testing to accurately determine the information that different users prefer. Due to the huge amount of data required for algorithm training, it often takes a day Therefore, the content recommendation based on this method fails to provide timely feedback on the user's current operation behavior, and it often takes until the next day to calculate the recommended content that the user is interested in. , making the recommendation effect unsatisfactory

Method used

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  • Content recommendation method and device, electronic device, and storage medium
  • Content recommendation method and device, electronic device, and storage medium
  • Content recommendation method and device, electronic device, and storage medium

Examples

Experimental program
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no. 1 example

[0029] Such as figure 1 as shown, figure 1 A structural block diagram of an electronic device 100 provided by an embodiment of the present invention is shown. The electronic device 100 includes: a content recommending apparatus 110 , a memory 120 , a storage controller 130 and a processor 140 . Wherein, in the embodiment of the present invention, the electronic device 100 may be, but not limited to, a network server, a database server, a cloud server, and the like.

[0030] The memory 120 , storage controller 130 , and processor 140 are electrically connected to each other directly or indirectly to realize data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines. The content recommendation apparatus 110 includes at least one software function module that can be stored in the memory 120 in the form of software or firmware (firmware) or solidified in the operating system...

no. 2 example

[0034] see figure 2 , is a content recommendation method applied to the above-mentioned electronic device 100 provided by the embodiment of the present invention, which will be combined below figure 2 Describe the steps involved.

[0035] Step S101: Determine the user's first interest preference based on the user's real-time browsing data.

[0036] Through open source content queues such as Kafka tools, the real-time browsing data of users is connected to the system for subsequent use, and the real-time browsing data of users in Kafka tools are obtained through the Spark-Streaming framework, and the user's first interest preference is determined. For example, if the current user is browsing a certain movie, the user's first interest preference may be determined based on characteristic information such as the type and theme of the movie. For another example, count the user's viewing volume of different types of content within a preset time period, and determine the user's f...

no. 3 example

[0058] The embodiment of the present application also provides a content recommendation device 110, such as Figure 4 shown. The content recommending device 110 includes: a first determining module 111 , a first generating module 112 and a recommending module 113 .

[0059] The first determination module 111 is configured to determine the user's first interest preference based on the user's real-time browsing data.

[0060] The first generating module 112 is configured to generate first recommended content according to the first interest preference.

[0061] The recommendation module 113 is configured to determine the final recommended content based on the first interest preference, the first recommended content, the second interest preference and the second recommended content, and recommend it to the user terminal, wherein the second interest preference is The interests and preferences determined in advance based on the historical browsing data of the user, the second reco...

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Abstract

The invention relates to a content recommendation method and device, an electronic device and a storage medium. The content recommendation method includes: determining a first interest preference of auser based on real-time browsing data of the user; Generating a first recommendation content according to the first interest preference; determining The final recommended content and recommending thecontent to the user terminal based on the first interest preference, the first recommended content, the second interest preference and the second recommended content, wherein the second interest preference is determined in advance based on the historical browsing data of the user, and the second recommended content is generated in advance according to the second interest preference. The method calculates the user's interest preference according to the real-time browsing data of the user, and recommends the content in real-time, which ensures the timeliness of the recommended content. At thatsame time, the recommend contents are modify according to the second interest preference determined in advance accord to the historical browsing data of the user and the generated second recommended contents, so that the new interests of the user can be captured in real time, and the more interesting contents can be recommended for the user.

Description

technical field [0001] The invention belongs to the technical field of the Internet, and in particular relates to a content recommendation method, device, electronic equipment and storage medium. Background technique [0002] With the development of Internet technology, there are more and more channels for people to obtain information. Various platforms provide users with information including articles, atlases, videos, etc. For platforms, how to recommend information that users are interested in to users is the key The first problem to face. The information recommended by the platform to users is often determined by various algorithms, and the algorithms need to undergo a large amount of data training and testing to accurately determine the information that different users prefer. Due to the huge amount of data required for algorithm training, it often takes a day Therefore, the content recommendation based on this method fails to provide timely feedback on the user's curr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/958G06F16/955
Inventor 余正阳
Owner 深圳墨世科技有限公司
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