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New Technology of Library and Information Service  2016, Vol. 32 Issue (7-8): 60-69    DOI: 10.11925/infotech.1003-3513.2016.07.08
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Discover Emerging Technologies with LDA Model
Ren Zhijun1,2(),Qiao Xiaodong1,Zhang Jiangtao2
1Institute of Scientific & Technical Information of China, Beijing 100038, China
2The China Patent Information Center, The State Intellectual Property Office, Beijing 100088, China
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[Objective] To identify emerging technologies from academic papers and patents. [Methods] We adopted the Latent Dirichlet Allocation (LDA) model to find technical topics and used the similarity theory to retrieve emerging technologies from the electric car data. [Results] The proposed method was more efficient than exisiting ones. It reduced the subjectivity of the experts’ evaluation and the amount of data to be analyzed. [Limitations] We did not include the expert scoring experiment in this study, thus, we could not compare the new model’s performance with those involving human judgements. [Conclusions] The proposed model could identify emerging technologies effectively and then reduce the document reading load of the experts.

Key wordsEmerging technology      Paper      Patent      Electric car      Technology similarity     
Received: 22 January 2016      Published: 29 September 2016

Cite this article:

Ren Zhijun,Qiao Xiaodong,Zhang Jiangtao. Discover Emerging Technologies with LDA Model. New Technology of Library and Information Service, 2016, 32(7-8): 60-69.

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