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Individual network news recommending method based on multitheme tracing

A news and theme technology, applied in the field of personalized news network push based on multi-theme tracking, can solve the problems of difficult data maintenance and management, inability to reflect user characteristics, etc.

Active Publication Date: 2010-04-14
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In order to overcome the shortcomings of the existing technology that adopting one user model cannot reflect user characteristics, and adopting multiple user models leads to difficulties in data maintenance and management, the present invention provides a method that can cover various interest characteristics of users, eliminating the need to use multiple user models Difficulties in data maintenance caused by it, and a personalized news network push method based on multi-theme tracking with good recommendation effect

Method used

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  • Individual network news recommending method based on multitheme tracing
  • Individual network news recommending method based on multitheme tracing
  • Individual network news recommending method based on multitheme tracing

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Embodiment Construction

[0032] With reference to accompanying drawing, further illustrate the present invention:

[0033] A personalized network news push method based on multi-topic tracking, comprising the following steps:

[0034] 1. Obtain the news webpages that the user has browsed, extract the title and text of each news webpage; use a clustering algorithm to divide the aforementioned news webpages into multiple news categories that the user is interested in, and use each news category as a sub-interest model, The sub-interest model is a vector composed of keyword information of all news reports in the model in for child interest model The weight information of the i-th keyword in all news reports in ; if the i-th keyword appears in multiple news reports, then is the sum of the weight information of the i-th keyword in each news report;

[0035] The news report is a vector composed of keyword information of the news report Corresponding keywords and their sub-interest models The key...

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Abstract

The invention relates to an individual network news recommending method based on multitheme tracing, which comprises the following steps: obtaining a news webpage browsed by a user and dividing the news webpage into a plurality of user interest submodels; dynamically updating a multitheme interest model of a user according to the condition that whether the user reads a news report recommended by the interest submodels or not; judging whether the quantity of the interest submodels exceeds a preset threshold value, if so, searching and deleting the interest submodel which is farthest from the interest of the user; searching the maximal similarity between news to be recommended and all the interest submodels; calculating sequencing values of the news report and sequencing the sequencing values from the large value to the small value; and recommending a sequenced news list to the user. The invention can cover various interest characteristics of the user and has the advantages of high recommending accuracy and lighter following maintenance burden of a system.

Description

technical field [0001] The invention relates to a news network push method, in particular to a personalized news network push method based on multi-theme tracking. Background technique [0002] With the rapid development of information communication technology, especially the continuous development and popularization of the Internet, the amount of information faced by human society is increasing at an alarming rate, and people have more and more needs for conveniently obtaining news information that they are interested in. more urgent. As a result, various news recommendation systems emerge in endlessly. [0003] The news recommendation system is an emerging software system developed on the Internet in recent years, which can push the latest news information to users in a proactive manner. Moreover, the recommendations given by the system are updated in real time, that is, as time goes by, the recommended news given will automatically change to the latest current informati...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 陈纯何占盈陈伟卜佳俊毛菥
Owner ZHEJIANG UNIV
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