Technological trends in mountain logistics: A patent analysis

Teshome, Mehari Beyene; Podrecca, Matteo; Orzes, Guido

doi:10.1016/j.rtbm.2024.101202

Research in Transportation Business & Management

2024

DOI: 10.1016/j.rtbm.2024.101202

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Technological trends in mountain logistics: A patent analysis

Mehari Beyene Teshome,

Matteo Podrecca,

Guido Orzes

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Patent Keyword Analysis Using Regression Modeling Based on Quantile Cumulative Distribution Function

Park,

Jun

2024

Electronics

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Patents contain detailed information of researched and developed technologies. We analyzed patent documents to understand the technology in a given domain. For the patent data analysis, we extracted the keywords from the patent documents using text mining techniques. Next, we built a patent document–keyword matrix using the patent keywords and analyzed the matrix data using statistical methods. Each element of the matrix represents the frequency of a keyword that occurs in a patent document. In general, most of the elements were zero because the keyword becomes a column of the matrix even if it occurs in only one document. Due to this zero-inflated problem, we experienced difficulty in analyzing patent keywords using existing statistical methods such as linear regression analysis. The purpose of this paper is to build a statistical model to solve the zero-inflated problem. In this paper, we propose a regression model based on quantile cumulative distribution function to solve this problem that occurs in patent keyword analysis. We perform experiments to show the performance of our proposed method using patent documents related to blockchain technology. We compare regression modeling based on a quantile cumulative distribution function with convenient models such as linear regression modeling. We expect that this paper will contribute to overcoming the zero-inflated problem in patent keyword analysis performed in various technology fields.

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Patent Keyword Analysis Using Regression Modeling Based on Quantile Cumulative Distribution Function

Park,

Jun

2024

Electronics

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scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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Technological trends in mountain logistics: A patent analysis

Cited by 1 publication

References 143 publications

Patent Keyword Analysis Using Regression Modeling Based on Quantile Cumulative Distribution Function

Patent Keyword Analysis Using Regression Modeling Based on Quantile Cumulative Distribution Function

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