Predicting citations to biotechnology patents based on the information from the patent documents

Lin, Bou Wen; Chen, Chung‐Jen; Wu, Hsueh Liang

doi:10.1504/ijtm.2007.013528

Cited by 29 publications

(15 citation statements)

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“…Lin, Chen, and Wu (2007) also surveys American patents over the 14 fields of biotechnology and presents that the nationality of applicant, geographical position, the number of claims are statistically associated with cited times. On the other hand, there is a positive or negative correlation between evaluation period and the cited times [20]. Our research differs from existing studies as follows.…”

Section: Related Literaturecontrasting

confidence: 68%

Patent Registration Prediction Methodology Using Multivariate Statistics

Jung

Park

Jang

2011

IEICE Trans. Inf. & Syst.

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Section: Related Literaturecontrasting

confidence: 68%

Patent Registration Prediction Methodology Using Multivariate Statistics

Jung

Park

Jang

2011

IEICE Trans. Inf. & Syst.

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“…It has been shown that technology domains with higher backward citations show higher growth [9]. In some studies based on technology sector or geography, a positive relationship was observed between backward citations and patent value [17,27]. Interestingly, other scholars did not identify this relationship [23,29,39].…”

Section: A Knowledge Accumulationmentioning

confidence: 97%

“…This is more an indication of its commercial value, and hence was not included in the combined patent value. Processing time has also been shown to be indicative of the overall patent value [27]. However, this kind of analysis can only be performed on granted patents.…”

Section: A Knowledge Accumulationmentioning

confidence: 99%

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Knowledge accumulation and value of inventions

Chandra

Dong

2015

2015 Portland International Conference on Management of Engineering and Technology (PICMET)

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A challenging task in technology management is the early identification of valuable inventions. Techniques that attempt to do so using patent indicators find that the predictions based on one indicator often do not agree with the predictions made with other indicators. Focusing on technological value, we propose a new metric based upon the concept of knowledge accumulation. Knowledge accumulation accounts for the background knowledge preceding the invention. Prior knowledge underlying an invention should be indicative of technical experience in the sector, which has led to solutions to various technological problems that grow the body of knowledge relevant to the invention. Hence knowledge accumulation may be a suitable indicator of the maturity of the knowledge that contributes to the specific invention. Using a composite patent value and multiple generation citation networks, we compare knowle�ge accumulation in patents for inventions in the energy harvestmg sector over a tOO-year observation period. The results indicate that there is a statistically significant correlation between . the composite patent value and knowledge accumulatIOn. As the analysis considered both patent applications and granted patents, the results imply that the metric can be used to predict the technological value of technologies that have not yet been patented.

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“…Tseng et al conducted a study to create a patent map using text mining techniques to analyze the relationship between each technology [5]. Subject to US 14 patents in the field of biotechnology, using a simple regression analysis, Lin, Chen and Wu revealed that the nationality of the patent applicant, geographic location and the number of claims are a statistically significant correlation with the number of citations while there is a positive or negative correlation between examination period and the number of citations partially [6]. Jun, Park and Jang used the patent data with method of support vector machine and patent matrix to predict the vacant technology in the field of Management of Technology [7].…”

Section: Related Literaturementioning

confidence: 99%

A Study on Forecasting System of Patent Registration Based on Bayesian Network

Kim¹,

Park²,

Jun

et al. 2012

IIM

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Recently the importance of intellectual property has been increased. There has been various ways of research on analysis of companies, forecast of technology and so on through patents and many investments of money and time. Unlike traditional method of patent analysis such as company analysis, forecasting technologies, this research is to suggest the ways to forecast registration and rejection of patents which help minimize the efforts to register patents. To do so, information such as inventors, applicants, application date, and IPC codes were extracted to be used as input variables for analyzing Bayesian network. Especially, among various forms of Bayesian network, we used Tree Augmented NBN (TAN) to forecast registration and rejection of patent. This is because, TAN was assumed to have dependence between variables. As a result of this Bayesian network, it was shown that there are nearly more than 80% of accuracy to forecast registration and rejection of patents. Therefore, we expect the minimization of time and cost of registration by forecasting registration and rejection of R&D patent through this research.

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Predicting citations to biotechnology patents based on the information from the patent documents

Cited by 29 publications

References 0 publications

Patent Registration Prediction Methodology Using Multivariate Statistics

Patent Registration Prediction Methodology Using Multivariate Statistics

Knowledge accumulation and value of inventions

A Study on Forecasting System of Patent Registration Based on Bayesian Network

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