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New Technology of Library and Information Service  2016, Vol. 32 Issue (3): 33-40    DOI: 10.11925/infotech.1003-3513.2016.03.05
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Identifying Research Trends Based on Patent Bibliographic Coupling: Case Study of Brain-Computer Interface
Gao Nan(),Fu Junying,Zhao Yunhua
Institute of Scientific & Technical Information of China, Beijing 100038, China
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[Objective] This study aims to identify the research trends (RT) based on patent bibliographic coupling method with the help of similarity algorithms. [Methods] We first established two types of patent similarity matrixes with two similarity algorithms - observed value (OV-BCA) and cosine distance (CD-BCA). We then used social network analysis to get the RT of Brain-Computer Interface (BCI) Patents. [Results] Six BCI research trend clusters were retrieved by OV-BCA algorithm, while CD-BCA algorithm got nine RT clusters. The two algorithms’ family ID coincidence rates were 43%. [Limitations] We focused on the comparison of results, including number, content and coincidence degree. More research is needed to study the characteristics of these algorithms. [Conclusions] RT can be retrieved by bibliographic coupling method with the help of the proposed algorithms. Specifically, the cosine distance algorithm can find more detailed research trends than the observed value algorithm.

Key wordsResearch trends      Patent      Bibliographic coupling analysis      Brian computer interface      Similarity algorithm     
Received: 29 September 2015      Published: 12 April 2016

Cite this article:

Gao Nan,Fu Junying,Zhao Yunhua. Identifying Research Trends Based on Patent Bibliographic Coupling: Case Study of Brain-Computer Interface. New Technology of Library and Information Service, 2016, 32(3): 33-40.

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