Multi-modal news recommendation method and device based on multi-head self-attention neural mechanism

A multi-modal and news technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of inaccurate modeling of news modeling users, high requirements for project information understanding, etc., to alleviate the cold start problem Effect

Pending Publication Date: 2022-03-08
BEIJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

However, this solution requires a high understanding of project information, and there are problems of inaccurate news modeling and user modeling

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  • Multi-modal news recommendation method and device based on multi-head self-attention neural mechanism
  • Multi-modal news recommendation method and device based on multi-head self-attention neural mechanism
  • Multi-modal news recommendation method and device based on multi-head self-attention neural mechanism

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Embodiment Construction

[0046]Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.

[0047] The multimodal news recommendation method and device based on the multi-head self-attention neural mechanism according to the embodiments of the present invention will be described below with reference to the accompanying drawings.

[0048] figure 1 It is a schematic flowchart of a multi-modal news recommendation method based on a multi-head self-attention neural mechanism provided by an embodiment of the present invention.

[0049] Such as figure 1 As shown, the multi-modal news recommendation method based on the multi-h...

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Abstract

The invention provides a multi-modal news recommendation method and device based on a multi-head self-attention neural mechanism, and the method comprises the steps: collecting data information, including news data, feature data and trace data; fusing the data information into uniform news features based on a multi-component feature cross model of a view-level attention mechanism, a hot news real-time prediction technology of streaming data and a multi-modal information fusion technology of intelligent frame extraction; and taking the unified news features as model input, and completing a personalized accurate recommendation function through a user interest representation model and in combination with a highest future influence strategy. According to the scheme, the user cold start problem is effectively relieved, feature collection and fusion are conducted on multi-modal information in news through multi-modal information fusion, high-order cross feature mining and user interest characterization learning are conducted through a multi-head self-attention mechanism, time sequence weights are given to the news according to the highest future influence strategy and real-time news hot spot mining, and the user interest characterization learning efficiency is improved. And participating in final user recommendation.

Description

technical field [0001] The invention belongs to the field of artificial intelligence. Background technique [0002] In today's information explosion and fast-paced society, more and more users acquire knowledge and information through online reading. In order to help users find correct and relevant content within a limited time, news recommendation technology emerges as the times require. News recommendation aims to solve the problem of information overload by making personalized recommendations to users through the computer's powerful computing power and high-efficiency feature matching. At present, there are mainly two forms of news recommendation methods: (1) filtering based on collaboration; (2) filtering based on content. [0003] (1) Based on collaborative filtering. Using the preferences of groups with similar interests and common experience to recommend information that users are interested in, individuals give a certain degree of response (such as scoring) to the...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9535G06F16/9536G06Q50/00
CPCG06F16/9535G06F16/9536G06Q50/01
Inventor 欧中洪刘沛航韩宗志宋美娜钟茂华梁昊光
Owner BEIJING UNIV OF POSTS & TELECOMM
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