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A personalized recommendation method for web text

A recommendation method and text technology, applied in unstructured text data retrieval, text database clustering/classification, special data processing applications, etc., can solve problems such as accuracy needs to be improved

Inactive Publication Date: 2017-08-11
YUNNAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] Although the existing Web text personalized recommendation method takes into account the historical data of user behavior, the accuracy of the recommendation still needs to be improved

Method used

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  • A personalized recommendation method for web text
  • A personalized recommendation method for web text
  • A personalized recommendation method for web text

Examples

Experimental program
Comparison scheme
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Embodiment

[0045] In this example, if figure 1 As shown, the Web text personalized recommendation method of the present invention comprises: step (1), Web text feature extraction, by word segmentation, keyword addition, keyword word frequency statistics, Web text is carried out feature extraction; Step (2), Web text model Construction, by generating a concept matrix of Web text collection based on the synonym forest, and then clustering to construct a Web text model; step (3), dynamic user preference modeling, according to the historical data of user behavior, that is, the behavior involved before time t A subset of Web texts, and its time information, based on the memory curve model, establishes a dynamic user preference model to express user preferences that change over time; step (4), personalized recommendation of Web texts, considering user preferences and Web text features The similarity, through the matching relationship to establish a user recommendation list to complete the pers...

example

[0099] Example: Personalized news recommendation based on user dynamic preferences

[0100] In this example, the web text is a news text. According to the historical behavior of users browsing news, given 5 news texts browsed by 2 users before February 1, 2015, including time information and news content, as shown in Table 1 , and related synonyms are shown in Table 2. On February 2, 2015, a new piece of news "Soldiers holding 95 rifles on guard to cover their companions' assault" was generated, which is a news text to be recommended.

[0101] Table 1 shows users, time, and online news text browsing data.

[0102]

[0103]

[0104] Table 1

[0105] Table 2 shows related synonyms Cilin.

[0106] words concept car vehicle SUV vehicle rifle arms Protect Protect

[0107] Table 2

[0108] (1), feature extraction of news text

[0109] Segment the content of the news text in Table 1, remove useless words, and extract keywords, a...

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Abstract

The invention discloses a method for a personalized recommendation of a Web text. The method comprises the following steps: performing feature extraction on a plurality of kinds of Web texts generated before a certain time t so as to obtain a feature matrix E of a Web text set, and then performing cluster so as to obtain n categories; besides, according to a time span hj from the time when a Web text oj in a Web text subset relevant to the behavior of a certain user ui before the time t to the time t, calculating out a preference influence degree dj to the user ui so as to obtain a pair of category number-influence degree cj of the Web text oj and generate a dynamic preference vector of the user ui; if the preference influence degree of the user and the category of the Web text to be recommended is found to be higher than or equal to a threshold value tan, recommending the Web text to be recommended to the user. According to the method disclosed by the invention, the dynamic influence changed with the time lapse of current preference from the historic behavior of the user is considered, and the method is more accurate in recommendation, has dynamic performance, and more conforms to the actual condition.

Description

technical field [0001] The invention belongs to the technical field of mass information processing and data mining, and more specifically, relates to a personalized recommendation method for Web texts, which obtains user preferences based on historical data of user behavior, and recommends Web texts of interest and potential interest to users. . Background technique [0002] The emergence and popularization of the Internet has met the needs of users for information in the information age, but the evolution of the network and the improvement of people's cognitive ability have accelerated the speed of information generation. [0003] Web text is a variety of Web information represented by text, such as network news, microblog content, text descriptions or evaluations of products on e-commerce websites, etc. are typical representatives of current Web texts. With the rapid development and popularization of Internet technology, a large number of Web texts have become an importan...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
CPCG06F16/337G06F16/35
Inventor 尹子都岳昆张骥先武浩刘惟一
Owner YUNNAN UNIV
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