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A Multi-source Personalized News Webpage Recommendation Method Based on Domain Ontology

A recommendation method and news technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of new users who have no historical information and cannot build configuration files, so as to improve accuracy and recall rate and ensure diversity performance, improving efficiency and accuracy

Active Publication Date: 2017-07-21
HEFEI UNIV OF TECH
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  • Description
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AI Technical Summary

Problems solved by technology

The disadvantage of this method is: how to recommend new users, because new users have no historical information and cannot build their corresponding configuration files

Method used

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  • A Multi-source Personalized News Webpage Recommendation Method Based on Domain Ontology
  • A Multi-source Personalized News Webpage Recommendation Method Based on Domain Ontology
  • A Multi-source Personalized News Webpage Recommendation Method Based on Domain Ontology

Examples

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Embodiment Construction

[0045] In this example, if figure 1 As shown, the domain ontology database of Chinese news contains news topics composed of first-level topics, second-level topics and third-level topics, and the first-level topics contain several first-level keywords T 1 , T 2 ,...,T n , the secondary subject contains several secondary subject words T 11 , T 12 ,...,T 21 , T 22 ,... T n1 ,..., the third-level topic contains several third-level topic words T 121 , T 122 ,...,T 421 , T 422 ,... T n21 ,…,Depend on figure 1 It can be known that the first-level theme is the parent category of the second-level theme, such as: T 1 is T 11 , T 12 ,... T 1m The parent class, the second-level theme is the parent class of the third-level theme, such as: T 12 is T 121 , T 122 ,... T 12p parent class. A first-level heading contains several second-level headings, such as T 1 contains T 11 , T 12 ,... T 1m various topics. A second-level heading contains several third-level headings,...

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Abstract

The invention discloses a multi-source individualized news webpage recommending method based on a field body. The method is characterized by comprising the following steps: 1, establishing a news corpus; 2, grabbing news; 3, establishing a user initial interest model; 4, establishing a news classification model; 5, performing individualized news recommendation; 6, updating the interest model. By adopting the method, the interest of a user can be mined, the accuracy and recall rate of a recommendation result are increased remarkably, and the satisfaction of the user is improved.

Description

technical field [0001] The invention belongs to the field of personalized recommendation, in particular to a multi-source personalized news recommendation method based on domain ontology. Background technique [0002] With the rapid development of the Internet, there are more and more ways for people to obtain information, and the information is growing explosively. Users are gradually shifting from information scarcity to an era of information overload—massive information makes it difficult for users to find the information they need. In order to make it easier for users to find what they need from massive amounts of information, many solutions have emerged: including catalogs and search engines. The classified directory is to classify commonly used popular websites into categories, which is convenient for users to find information. However, as the scale of the Internet expands, classified directories can only cover a small number of popular websites. Search engines allow...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30G06F17/27
CPCG06F16/9535
Inventor 吴信东谢飞胡学钢宫雪郭建波
Owner HEFEI UNIV OF TECH
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