Film and television resource personalized recommendation method in a social network environment

A technology of film and television resources and social network, which is applied in the field of personalized recommendation of film and television resources, can solve problems such as influence, and achieve the effect of accurate emotional tendency and precise recommendation

Active Publication Date: 2021-07-23
HUNAN UNIV OF TECH
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  • Summary
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  • Description
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AI Technical Summary

Problems solved by technology

However, the PLTS-VIKOR method assumes that the decision-maker is completely rational,

Method used

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  • Film and television resource personalized recommendation method in a social network environment
  • Film and television resource personalized recommendation method in a social network environment
  • Film and television resource personalized recommendation method in a social network environment

Examples

Experimental program
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Effect test

Embodiment 1

[0060] like figure 1 As shown, a method for personalized recommendation of video resources in a social network environment includes the following steps:

[0061] S1: Online review acquisition and preprocessing. The present invention uses the octopus collector to obtain the movie online review data on the Rotten Tomatoes website, and obtains a total of 11957 online reviews, of which AvengersEndgame (x 1 ) 2219, KnivesOut(x 2 ) 2589, Parasite (Gisaengchung) (x 3 ) 2436, ToyStory4(x 4 )2352, Us(x 5 ) 2361. Since the obtained original online comment data may have words that are irrelevant to the viewer's attitude, repeated and invalid, the present invention uses the python library-Natural Language Toolkit (NLTK) to preprocess the online comment data to perform Remove stop words, lemmatization, synonyms and other operations.

[0062] S2: Calculation of online comment sentiment value:

[0063] S2.1: Use the natural language library TextBlob to calculate the sentiment value o...

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Abstract

The invention discloses a film and television resource personalized recommendation method in a social network environment, and belongs to the technical field of data analysis and pushing. The method includes the following steps of S1, online comment obtaining and preprocessing, S2, online comment emotion value calculation, S3, film watching decision criterion and weight determination, and S4, film and television resource sorting: a comprehensive foreground value of a film xi is obtained by combining a probability language decision matrix, a value function and a weight function, wherein the larger the comprehensive foreground value is, the more worthy of recommendation is achieved, and the higher the sorting is. According to the method, the influence of irrational factors such as psychological behaviors of film viewers on decision making of the film viewers is fully considered while objective factors are considered, so that film and television resource recommendation is more practical and accurate.

Description

technical field [0001] The invention belongs to the technical field of data analysis and pushing, and more specifically, relates to a method for personalized recommendation of film and television resources in a social network environment. Background technique [0002] In the field of film and television resource recommendation, the universality of object-oriented determines the complexity of the recommendation work. The recommendation of film and television resources should not only pay attention to changes in the political environment, economic environment, and social environment, but also fully consider the individual needs of movie viewers. Different movie viewers often have different concerns for the same film and television resources. Its evaluation will also vary widely. Especially in this era of rapid Internet development, the online comment data of movie viewers is growing explosively. In order to ensure the efficiency and accuracy of film and television resource re...

Claims

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Application Information

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IPC IPC(8): G06F16/735G06F16/9535
CPCG06F16/735G06F16/9535
Inventor 周欢马浩南
Owner HUNAN UNIV OF TECH
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