Digital content resource value evaluation method based on GCA-RFR model

A technology for digital content and value evaluation, applied in computing models, biological models, market forecasting, etc., can solve problems such as the difficulty of distinguishing specific values, the difficulty of measuring subjective factors, and the lack of uniform standards for defining value evaluation

Pending Publication Date: 2020-09-18
BEIJING INFORMATION SCI & TECH UNIV
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Problems solved by technology

[0003] At present, there are mainly the following problems in the transaction of content resources in my country: ①The quality of digital content resources is uneven, and there is no clear publishing standard; ②Most of them are bundled with other services (such as advertisement

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  • Digital content resource value evaluation method based on GCA-RFR model
  • Digital content resource value evaluation method based on GCA-RFR model
  • Digital content resource value evaluation method based on GCA-RFR model

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Embodiment Construction

[0060] The following is attached Figure 1-3 The present invention is described in further detail.

[0061] In order to solve the problems existing in the prior art, the present invention proposes a digital content resource value evaluation method based on gray relational analysis and random forest regression GCA-RFR model.

[0062] Firstly, the "value chain theory" is used as the main line to explore the influencing factors of the value of digital content resources, and based on this, the value evaluation index system of digital content resources is constructed; secondly, the generalized gray relational analysis method is used to verify and screen the evaluation indicators, and through the entropy value- Deng's gray relational analysis method is used to screen the initial samples; finally, the random forest regression RFR model is used for training, and the value evaluation method of digital content resources is constructed by continuously optimizing the model.

[0063] Such...

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Abstract

The invention discloses a digital content resource value evaluation method based on grey correlation analysis and a random forest regression GCA-RFR model, and the method comprises the steps: taking avalue chain theory as a main line to explore an influence factor of a content resource value, and constructing a content resource value evaluation index system according to the influence factor; crawling related data of an Internet movie database by means of Python, and cleaning the data by deleting and replacing the data cells to obtain valid data; performing index verification and screening byusing a generalized grey correlation analysis method to obtain a final effective index system; carrying out initial sample screening based on an entropy-Dane grey correlation analysis method, and obtaining a final sample set for model training; and based on the index system and the training data, continuously optimizing a random forest regression RFR model to construct a digital content resource value evaluation method. According to the invention, a digital content resource value evaluation function is realized, and the method has high scientificity, effectiveness and wide applicability.

Description

technical field [0001] The invention belongs to the field of standardized content resource transactions, and relates to a digital content resource value evaluation method based on gray relational analysis and random forest regression model (GCA-RFR). Background technique [0002] According to the "2017-2018 Annual Report on China's Digital Publishing Industry", the digital publishing industry has surpassed "traffic is king" and reached a new era of "content is king", and content production is gradually becoming more specialized and high-quality. With the establishment of 10 national standards such as "Data Processing of Content Resources", digital content publishing will become increasingly standardized. In addition, the operation ecology of Internet literature IP (IntellectualProperty) is gradually mature. On the basis of paper books, it is not uncommon to develop diversified content IP development models such as movies, TV dramas, animations, and games. However, as an eme...

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Application Information

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IPC IPC(8): G06Q30/02G06N3/00
CPCG06Q30/0206G06N3/006
Inventor 倪渊蔡功山赵艳张健杨露高宇东高霞
Owner BEIJING INFORMATION SCI & TECH UNIV
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