Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A news recommendation method based on knowledge perception

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

Active Publication Date: 2022-05-27
BEIJING INSTITUTE OF TECHNOLOGYGY
View PDF4 Cites 0 Cited by
  • Summary
  • 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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A news recommendation method based on knowledge perception
  • A news recommendation method based on knowledge perception
  • A news recommendation method based on knowledge perception

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

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

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

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

[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 validation experiments on the BingNews dataset. Each record in the dataset contains information such as user ID, news headline, whether the user clicked, and a 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 technology to link and disambiguate the words in the news text with the entities in the knowledge graph to obtain a news entity set.

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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a news recommendation method based on knowledge perception, which belongs to the technical field of artificial intelligence and network information big data. Firstly, entities are identified from news texts, matched with entities in the knowledge graph, and vector representations of entities and relationships are obtained using the knowledge representation learning model. Then, a convolutional neural network is used to fuse word vectors and entity vectors of news, and learn comprehensive features of news from them. For each news candidate, based on the correlation between the user's browsing history and the news candidate, user features are dynamically constructed using an attention network. At the same time, considering the path between the entity in the clicked news and the entity in the candidate news, the long short-term memory network is used to generate path features from the path. Finally, with the candidate news features, user features and path features as input, the multi-layer perception mechanism is used to calculate the probability of the user clicking on the candidate news to achieve the purpose of recommendation. The invention can effectively excavate the knowledge association between news, which is significantly better than the traditional method.

Description

technical field [0001] The invention relates to a news recommendation method based on knowledge perception, belonging 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 and 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 context of news recommendation, the following points need to be paid attention to: First, news has a strong timeliness and changes quickly, so traditional collaborative filtering methods are not applicable. Second, users are usually interested in news content of some specific topics. How to build an interest preference model for users according to the user's browsing history, and determine whether the ca...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(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
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com