Using Patent Data for Technology Analysis and Planning

Mogee, Mary Ellen

doi:10.1080/08956308.1991.11670755

Cited by 145 publications

(67 citation statements)

References 4 publications

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“…Patent data are highly efficient to search and analyze because the patent specification format is standardized [38,39]. In addition, patent data include bibliographic information in addition to technical information, so various analyses are possible.…”

Section: Data Collection and Sao Structure Extractionmentioning

confidence: 99%

SAO-Based Semantic Mining of Patents for Semi-Automatic Construction of a Customer Job Map

et al. 2017

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Abstract:The Outcome-Driven Innovation (ODI) method based on the 'Jobs-to-be-done' concept is very useful in the identification of unmet customer needs and has been adopted widely in the industry. The Job Map, a tool of the ODI method, is used to understand customers by defining their behavioral process. Complications must be overcome before the Job Map can be applied to the specific problem in question, such as a time-consuming process, dealing with a large amount of data, and experts' biased work. To solve these problems, this study develops a patent mining-based method based on the subject-action-object (SAO) structure to support the creation of a Job Map by semi-automatizing data collection and analysis. This effort at better utilizing computers in customer analysis for product design will contribute to expanding computerized methods for solving design and engineering problems in practice.

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Section: Data Collection and Sao Structure Extractionmentioning

confidence: 99%

SAO-Based Semantic Mining of Patents for Semi-Automatic Construction of a Customer Job Map

et al. 2017

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“…In recent years, there have been studies using technical indicators that represent the technological capability of a company as predictors to predict corporate performance [16][17][18]37]. Many of these studies apply patent data to derive the technical indicators [16][17][18][19][20][21][22]37]. We collected 59,740 patent data items on 22 pharmaceutical companies in order to derive the technical indicators of companies' technological capability.…”

Section: Predictors Of the Proposed Prediction Modelmentioning

confidence: 99%

“…As a result, many recent studies have proposed indicators that show the technological competitiveness of a company [16][17][18]. Many of these studies apply patent data, because they are easy to use in quantitative analyses, have an internationally uniform structure, and contain citation information [19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning-Based Corporate Performance Prediction Model Considering Technical Capability

2017

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Many studies have predicted the future performance of companies for the purpose of making investment decisions. Most of these are based on the qualitative judgments of experts in related industries, who consider various financial and firm performance information. With recent developments in data processing technology, studies have started to use machine learning techniques to predict corporate performance. For example, deep neural network-based prediction models are again attracting attention, and are now widely used in constructing prediction and classification models. In this study, we propose a deep neural network-based corporate performance prediction model that uses a company's financial and patent indicators as predictors. The proposed model includes an unsupervised learning phase and a fine-tuning phase. The learning phase uses a restricted Boltzmann machine. The fine-tuning phase uses a backpropagation algorithm and a relatively up-to-date training data set that reflects the latest trends in the relationship between predictors and corporate performance.

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“…In the study "Using patent data for technology analyses and planning" Mary Ellen Mogee notes that patents have several advantages as a "technology indicator" [3]. It is important to note that the average ratio between the number of patents and the number of jobs in the computer manufacturing industry is 55.5 patents per year for 1,000 jobs in the chemical industry is already 16 patents per year for 1,000 jobs in the production of plastic 10, 2 patents for 1,000 jobs, and in the food industry 0.1 patents per year for 1,000 jobs.…”

Section: Patens As a Data Source Of The Technological Trends Monitoringmentioning

confidence: 99%

Study of The Correlation Between World Patenting Trends and The University Admission Rate in Russia Based on Open Data

2016

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Abstract. This paper discusses use of the open PCT patent data and university admission rate to study world technological trends and correlation between industry trends and the student admission rate for government sponsored University programs in Russia. OECD open statistical database and Lomonosov Moscow State University open admission data is used as a data source in this study. ICT and biotechnology industries used as a sample industries to study this correlations.

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Using Patent Data for Technology Analysis and Planning

Cited by 145 publications

References 4 publications

SAO-Based Semantic Mining of Patents for Semi-Automatic Construction of a Customer Job Map

SAO-Based Semantic Mining of Patents for Semi-Automatic Construction of a Customer Job Map

Deep Learning-Based Corporate Performance Prediction Model Considering Technical Capability

Study of The Correlation Between World Patenting Trends and The University Admission Rate in Russia Based on Open Data

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