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Method and device for training recommendation model, and recommendation system

A model and information recommendation technology, applied in the Internet field, can solve the problems of time-consuming and labor-intensive selection of interaction items, inability to discover interactions, and low technical efficiency, so as to improve the prediction accuracy, reduce the amount of sample data, and save storage space.

Active Publication Date: 2016-05-18
CHEZHI HULIAN BEIJING SCI & TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Under the premise of having a large number of users and limited hardware resources, most current click-through rate estimation systems still use the linear model (LR) for model training. The selection of interactive items is time-consuming and laborious
In addition, the existing technical solutions, which use huge sample features to train the recommendation model, will take up a lot of resources and have low technical efficiency

Method used

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  • Method and device for training recommendation model, and recommendation system
  • Method and device for training recommendation model, and recommendation system
  • Method and device for training recommendation model, and recommendation system

Examples

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Embodiment Construction

[0033] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0034] figure 1A schematic diagram of an exemplary recommendation system 100 according to the present invention is shown. When a user browses pages at all levels of a website (such as a car home, etc.) or a user searches for pages related to keywords entered by a search engine, the recommendation system 100 is suitable for recommending to the pages at all levels browsed by the user or the pages queried. Add recommended information...

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Abstract

The invention discloses a method and a device for training a recommendation model, and a recommendation system. The device for training the recommendation model comprises a log acquisition unit, a first characteristic extraction unit, a second characteristic extraction unit, a sample generation unit, a sample aggregation unit and a model training unit, wherein the log acquisition unit is suitable for acquiring a plurality of access logs; the first characteristic extraction unit is suitable for extracting a first characteristic used for identifying recommendation information which presents on a corresponding page of each access log from each access log, and extracting a second characteristic used for identifying the context information of the page; and the second characteristic extraction unit is suitable for acquiring the interest degree sorting value of the user associated with each access log on various pieces of recommendation information, inquiring the interest degree sorting value corresponding to the recommendation information which presents on the corresponding page of the access log, and taking the acquired interest degree sorting value as a third characteristic.

Description

technical field [0001] The invention relates to the Internet field, in particular to a method, device and recommendation system for training a recommendation model. Background technique [0002] With the rapid development of the Internet, website platforms (such as Autohome) can provide a large amount of content such as information, news, advertisements, etc., to meet users' needs for information. However, when users are faced with a large amount of information, it is difficult to obtain the part that they are really interested in. [0003] Generally speaking, when a user browses a webpage through a search engine or directly on a website, information recommended to the user may be displayed on the webpage. The website platform can select the information to be recommended through the recommendation system. For example, the recommendation system can determine the probability of the recommended information being clicked by the user through the way of predicting the click rate...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 王亚龙
Owner CHEZHI HULIAN BEIJING SCI & TECH CO LTD
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