News recommendation method based on knowledge perception

A recommendation method and news technology, applied in neural learning methods, biological neural network models, instruments, etc., can solve the problem that news recommendation models are difficult to capture knowledge associations

Active Publication Date: 2020-04-24
BEIJING INSTITUTE OF TECHNOLOGYGY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the existing news recommendation model based on text features is difficult to capture the hidden knowledge association in the text, and creatively propose a news recommendation method based on knowledge perception

Method used

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  • News recommendation method based on knowledge perception
  • News recommendation method based on knowledge perception
  • News recommendation method based on knowledge perception

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Embodiment Construction

[0014] The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0015] Such as figure 1 As shown, a knowledge-based news recommendation method includes the following steps:

[0016] Step 1: Divide the dataset into training set and test set.

[0017] Among them, the training set is used to optimize the parameters, and the test set is used to test the effect.

[0018] For example, by implementing a validation experiment on the BingNews dataset. Each record in the dataset contains information such as user ID, news title, whether the user clicked, and timestamp.

[0019] Step 2: Extract entity knowledge information in news text.

[0020] Specifically include the following steps:

[0021] Step 2.1: Use the entity linking technique to link and disambiguate the words in the news text and the entities in the knowledge graph to obtain a news entity set.

[0022] Step 2.2: Based on the news entity set, a knowledge gra...

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Abstract

The invention discloses a news recommendation method based on knowledge perception, and belongs to the technical field of artificial intelligence and network information big data. The method comprisesthe following steps: firstly, identifying entities from a news text, matching the entities with entities in a knowledge graph, and obtaining vector representation of the entities and relationships byutilizing a knowledge representation learning model; secondly, fusing the word vectors and the entity vectors of the news through a convolutional neural network, and learning comprehensive features of the news from the word vectors and the entity vectors; for each piece of candidate news, dynamically constructing user features by using an attention network based on the correlation between the user browsing history and the candidate news, meanwhile, considering paths between entities in clicked news and entities in candidate news, and generating path features from the paths through a long-termand short-term memory network; finally, taking the candidate news features, the user features and the path features as input, and calculating the probability that the user clicks the candidate news by using a multi-layer perception mechanism to achieve a recommendation purpose. Knowledge association between news can be effectively mined, and the method is remarkably superior to a traditional method.

Description

technical field [0001] The invention relates to a news recommendation method based on knowledge perception, which belongs to the technical field of artificial intelligence and network information big data. Background technique [0002] With the popularity of the mobile Internet, more and more people choose to obtain news information through the mobile Internet. For news content platforms, it is very important to build a personalized news recommendation system that can capture users' reading interests and push relevant information to them. [0003] Generally speaking, in the news recommendation scenario, the following points need to be paid attention to: First, news is highly time-sensitive and changes quickly, so traditional collaborative filtering methods are not applicable. Second, users are usually interested in the news content of some specific topics. How to build an interest preference model for users based on the user's browsing history and judge whether candidate ne...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/335G06F16/36G06F16/9535G06N3/04G06N3/08
CPCG06F16/335G06F16/367G06F16/9535G06N3/08G06N3/045
Inventor 刘琼昕覃明帅宋祥王佳升徐建祥卢士帅
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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