Algorithms for big data mining of hub patent transactions based on decision trees DOI Creative Commons

Aleksandr Zhukov,

Sergey Pronichkin,

Yuri Mihaylov

и другие.

EPJ Web of Conferences, Год журнала: 2025, Номер 318, С. 04013 - 04013

Опубликована: Янв. 1, 2025

Dysfunctions of the patent supply and demand market have a negative impact on sustainability national innovation system, which stimulates growth prices for knowledge-intensive products. It is necessary to establish relationship between fiscal decisions regarding transactions prospects development commercialization results intellectual activity. One most promising methods improving accuracy system analysis big semi-structured transaction data use decision trees. Existing based error backpropagation method are quite slow, their accelerated versions lose in training accuracy. To effectively solve problem forecasting cost hub transactions, parametric algorithms been developed response bias with additional predicative structures model successive geometric transformations. The optimal number tree predicates has established taking into account computational efforts transactions. Based evolutionary computing, values parameters mining established.

Язык: Английский

Algorithms for big data mining of hub patent transactions based on decision trees DOI Creative Commons

Aleksandr Zhukov,

Sergey Pronichkin,

Yuri Mihaylov

и другие.

EPJ Web of Conferences, Год журнала: 2025, Номер 318, С. 04013 - 04013

Опубликована: Янв. 1, 2025

Dysfunctions of the patent supply and demand market have a negative impact on sustainability national innovation system, which stimulates growth prices for knowledge-intensive products. It is necessary to establish relationship between fiscal decisions regarding transactions prospects development commercialization results intellectual activity. One most promising methods improving accuracy system analysis big semi-structured transaction data use decision trees. Existing based error backpropagation method are quite slow, their accelerated versions lose in training accuracy. To effectively solve problem forecasting cost hub transactions, parametric algorithms been developed response bias with additional predicative structures model successive geometric transformations. The optimal number tree predicates has established taking into account computational efforts transactions. Based evolutionary computing, values parameters mining established.

Язык: Английский

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