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Project recommendation method and device, project recommendation model, medium and electronic equipment

A project recommendation and model technology, applied in the field of artificial intelligence, can solve problems such as low recommendation accuracy

Pending Publication Date: 2022-07-12
TENCENT TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, when recommending items through solutions provided by related technologies, the recommendation accuracy is low

Method used

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  • Project recommendation method and device, project recommendation model, medium and electronic equipment
  • Project recommendation method and device, project recommendation model, medium and electronic equipment
  • Project recommendation method and device, project recommendation model, medium and electronic equipment

Examples

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Embodiment Construction

[0047] Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments, however, can be embodied in various forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art.

[0048] Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided in order to give a thorough understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be employed. In other instances, well-known m...

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Abstract

The invention relates to the technical field of artificial intelligence, and provides an item recommendation method and device based on reinforcement learning, a model, a medium and equipment. The method comprises the steps that a recommendation value of a target item is predicted according to vector representation of the target item and historical browsing items in a current item list, and the current item list is composed of items containing user browsing behaviors; obtaining a relative feature between the target item and the historical browsing item; based on a reinforcement learning model, determining whether the current item list needs to be filtered or not according to the relative features and the recommendation values; and in response to the need of filtering the current item list, determining to-be-filtered items in the current item list according to the relative characteristics based on the reinforcement learning model, so as to perform item recommendation based on the filtered optimized item list. According to the technical scheme, whether the current item list needs to be filtered or not can be quickly and effectively distinguished, the to-be-filtered item can be determined, and the item recommendation accuracy can be improved.

Description

technical field [0001] The present disclosure relates to the technical field of artificial intelligence, and in particular, to a reinforcement learning-based item recommendation method and device, an item recommendation model, and a computer-readable storage medium and electronic device for implementing the above reinforcement learning-based item recommendation method. Background technique [0002] With the development of artificial intelligence technology, the recommendation system predicts the content that the user may like through the prediction model, so as to recommend the content to the user that meets the user's personalized needs. For example, recommend songs that users may like for song listening users, and recommend content that users may like for video / short video viewers. [0003] In the related art, historical browsing data of multiple users is generally obtained first, and then a prediction model is trained based on the historical browsing data. Further, recom...

Claims

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Application Information

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IPC IPC(8): G06F16/9535G06N20/00
CPCG06F16/9535G06N20/00
Inventor 陈昊
Owner TENCENT TECH (SHENZHEN) CO LTD
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