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Product functional information based automatic patent classification: Method and experimental studies

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journal contribution
posted on 2018-05-29, 13:19 authored by Wen-qiang Li, Yan Li, Jian Chen, Chao-yi Hou
In order to effectively extract the hidden information from the patent texts and to further provide this information to support the product innovation design process, this paper proposed an automatic patent classification method based on the functional basis and Naive Bayes theory. The functions of products are regarded as the innovation attributes, and the function co-reference relations of the patents in different areas are established. Patent classification methods are proposed based on the functions of products and the general steps of the patent classification process are proposed. In addition, three training methods are studied in the experiments, including multi-classification fully supervised training, multiple dichotomous supervised training and semi-supervised training. Through comparing and analyzing the experimental results, a patent text classifier is developed. In summary, this paper provides a general idea and the relevant technologies on how to build a patent knowledge space by automatically extracting and expanding the patent texts.

Funding

This work is supported by the National Natural Science Foundation of China (Grant No. 51435011).

History

Citation

Information Systems, 2017, 67, pp. 71-82

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Engineering

Version

  • AM (Accepted Manuscript)

Published in

Information Systems

Publisher

Elsevier

issn

0306-4379

Acceptance date

2017-03-27

Copyright date

2017

Available date

2019-03-29

Publisher version

https://www.sciencedirect.com/science/article/pii/S0306437916301594?via=ihub

Notes

The file associated with this record is under embargo until 24 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.

Language

en

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