Item recommendation model training method, item recommendation method and device

A technology for item recommendation and model training, applied in the field of deep learning, which can solve the problems of low recommendation accuracy, inability to describe the overall interests and current interests of users, etc.

Active Publication Date: 2019-02-26
GUOXIN YOUE DATA CO LTD
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Problems solved by technology

When these models are applied to item recommendation, there are also problems such as the inability to d

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  • Item recommendation model training method, item recommendation method and device
  • Item recommendation model training method, item recommendation method and device
  • Item recommendation model training method, item recommendation method and device

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[0048] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only It is a part of the embodiments of this application, not all of them. The components of the embodiments of the application generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations. Accordingly, the following detailed description of the embodiments of the application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of the application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without...

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Abstract

The invention discloses an item recommendation model training method, an item recommendation method and device. The item recommendation model training method of the invention comprises the following steps: generating a first representation vector of each user and a second representation vector of each item based on at least one user's operation information of at least one item; selecting at leastone sample user, the at least one sample user being part or all of the at least one user; and generating, for each of the at least one sample user, training data of the item recommendation model basedon an order of operation of the item operated by the sample user and a second representation vector of the item operated by the sample user, and a first representation vector of the sample user; training the item recommendation model by using the training data. The present application can better describe the user's interest preference, improve the effectiveness of the model, and improve the accuracy of project recommendation using the model.

Description

technical field [0001] The present application relates to the technical field of deep learning, and specifically relates to an item recommendation model training method, an item recommendation method and a device. Background technique [0002] In the item recommendation problem, it is necessary to consider the order in which users operate on different items, which plays an important role in learning the user's current interest preferences. [0003] Current modeling methods based on sequential relationships, such as Hidden Markov Model (HMM), Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM), etc. There are still problems such as missing sequence information and difficult training. When these models are applied to item recommendation, there will also be problems such as the inability to describe the user's overall interest and current interest, and the accuracy of recommendation is not high. Contents of the invention [0004] In view of this, the purpose o...

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Application Information

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IPC IPC(8): G06K9/62G06Q10/10
CPCG06Q10/103G06F18/2411G06F18/214
Inventor 王惠照郑凯段立新江建军
Owner GUOXIN YOUE DATA CO LTD
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