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Information recommendation method and device, electronic equipment and computer storage medium

A technology of information recommendation and topic information, applied in the computer field, can solve the problems of inability to understand the real needs of users, lack of commodities and users' deeper cognition, etc., and achieve the effect of comprehensive and rich information.

Pending Publication Date: 2020-06-30
ALIBABA GRP HLDG LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing recommendation systems only recommend information related to the user's search, such as only recommending products related to "crutches" or products related to "conversion joints", but lack a deeper understanding of products and users , so that it is impossible to understand the real needs of the user's multi-intent expression

Method used

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  • Information recommendation method and device, electronic equipment and computer storage medium
  • Information recommendation method and device, electronic equipment and computer storage medium
  • Information recommendation method and device, electronic equipment and computer storage medium

Examples

Experimental program
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Embodiment 1

[0022] refer to figure 1 , shows a flow chart of steps of an information recommendation method according to Embodiment 1 of the present invention.

[0023] The information recommendation method of this embodiment includes the following steps:

[0024] Step S102: Obtain the first type of user information used to indicate the user's real-time behavior and the second type of user information used to indicate the user's demand scenario.

[0025] The first type of user information is used to indicate the real-time behavior of the user. The real-time behavior of the user is different for different behavior objects. For example, for e-shopping applications, the real-time behavior of the user may include but not limited to: Additional purchase (adding to shopping cart), browsing, sharing, etc.; for e-book applications, the real-time behavior of users may include but not limited to: reading, previewing, purchasing, marking, adding bookmarks, sharing, etc.; for news applications, The ...

Embodiment 2

[0040] refer to figure 2 , shows a flow chart of steps of an information recommendation method according to Embodiment 2 of the present invention.

[0041] The information recommendation method of this embodiment includes the following steps:

[0042] Step S202: Construct an inference path according to an inference rule.

[0043] In this embodiment, in order to simplify the specific implementation of inference rules and reduce the implementation cost of the overall solution, a directed graph structure is used to realize the first inference rule and the second inference rule. Therefore, before performing information recommendation operations, it is necessary to first construct a directed graph according to inference rules, and the directed graph includes a first inference path corresponding to the first inference rule and a second inference path corresponding to the second inference rule.

[0044] In this embodiment, the first inference rules for constructing the first infer...

Embodiment 3

[0097] refer to Figure 4 , shows a structural block diagram of an information recommendation device according to Embodiment 3 of the present invention.

[0098] The information recommendation device in this embodiment includes: a first acquisition module 302, configured to acquire the first type of user information used to indicate the user's real-time behavior and the second type of user information used to indicate the user's demand scene; the second acquisition module 304, Obtaining at least one corresponding first subject information according to at least one first inference rule corresponding to the first type of user information, and, according to at least one second inference rule corresponding to the second type of user information, Obtain at least one corresponding second topic information; recommendation module 306, configured to determine topic information to be recommended from the first topic information and the second topic information, and perform information r...

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Abstract

The embodiment of the invention provides an information recommendation method and device, electronic equipment and a computer storage medium, and the method comprises the steps: obtaining a first typeof user information for indicating a real-time behavior of a user and a second type of user information for indicating a user demand scene; according to at least one first reasoning rule corresponding to the first type of user information, obtaining at least one piece of corresponding first theme information, and according to at least one second reasoning rule corresponding to the second type ofuser information, obtaining at least one piece of corresponding second theme information; and determining to-be-recommended theme information from the first theme information and the second theme information, and performing information recommendation operation according to the determined theme information. Through the embodiment of the invention, the information recommendation efficiency is improved, and the use experience of the user is also improved.

Description

technical field [0001] The embodiments of the present invention relate to the field of computer technology, and in particular to an information recommendation method, device, electronic equipment, and computer storage medium. Background technique [0002] With the rapid development of the network, the amount of information on the Internet has increased significantly, making it impossible for users to obtain the part of information that is really useful to them when faced with a large amount of information, resulting in a decrease in the efficiency of information use. For this reason, recommender systems came into being. [0003] The recommendation system is a personalized information recommendation system that recommends the information and products that the user is interested in to the user according to the user's information needs and interests. It conducts personalized calculations by studying the user's interest preferences, and the system discovers the user's points of...

Claims

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Application Information

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IPC IPC(8): G06F16/9535G06N5/04
CPCG06F16/9535G06N5/04
Inventor 杨可苹王锦关龙飞龚剑波宣芸芸林古立林泉吴敏龙张鑫李淼越杨勇华袁怀宾
Owner ALIBABA GRP HLDG LTD
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