Open Access

The Application of Artificial Intelligence Technology in Intellectual Property Protection and Its Impact on the Cultural Industry

 and   
Feb 03, 2025

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Figure 1.

Patent data mining flow chart
Patent data mining flow chart

Figure 2.

Data collection characteristics extraction rate training results
Data collection characteristics extraction rate training results

Figure 3.

The number of patents published between 2010 and 2020
The number of patents published between 2010 and 2020

Figure 4.

The results of the training loss in the training data set
The results of the training loss in the training data set

Figure 5

Classification of clothing appearance patent data set
Classification of clothing appearance patent data set

Figure 6.

Classification characteristics statistics accuracy
Classification characteristics statistics accuracy

Figure 7.

Different path patent intellectual property protection index trend
Different path patent intellectual property protection index trend

Clothing intellectual property protection index and weight

Primary indicator Secondary indicator Weight
Judicial protection index Legislative index 12.33
Judgment index 10.94
Execution index 6.73
Administrative index Market access index 16.75
According to the administrative index of law 11.28
Market supervision index 6.97
Social protection index Social environment index 12.26
Network environment index 15.14
Human environmental index 7.60
Total 100

The test set is evaluated

Cluster search width Evaluation index DP-MVGCN CNN+LSTM VGG16+LSTM
K=1.5 Category description 89.61 72.1 72.55
Color description 97.43 83.42 86.18
Material description 89.45 71.73 77.98
Design feature description 91.88 88.53 86.17
Cross validation 99.05 90.45 91.3
K=3.0 Category description, 97.49 90.67 89.95
Color description 99.87 89.65 92.86
Material description 95.29 83.26 85.55
Design feature description 95.73 88.73 86.82
Cross validation 99.55 91.74 90.15
Language:
English