Abstract
The application of big data mining can create over a trillion dollars value. Patents contain a great deal of new technologies and new methods which have unique value in the product innovation. In order to improve the effectiveness of big data mining and aid the innovation of products of forestry machinery, the algorithm for closed weighted pattern mining is applied to acquire the function knowledge in the patents of forestry machinery. Compared with the other algorithms for mining patterns, the algorithm is more suitable for the characteristics of patent data. It not only takes into account the importance of different items to reduce the search space effectively, but also avoids achieving excessive uninteresting patterns below the premise that assures quality. The extensive performance study shows that the patterns which are mined by the closed weighted pattern algorithm are more representative and the acquired knowledge has more realistic application significance.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kang, B., Motohashi, K.: The role of essential patents as knowledge input for future R&D. World Patent Information 05, 1–9 (2014)
Seol, H., Lee, S., Kim, C.: Identifying new business areas using patent information: A DEA and text mining approach. Expert Systems with Applications 38, 2933–2941 (2011)
Wang, W.M., Cheung, C.F.: A Semantic-based Intellectual Property Management System (SIPMS) for supporting patent analysis. Engineering Applications of Artificial Intelligence 24, 1510–1520 (2011)
Zhang, H., Qiu, Q., Feng, P., Wang, Z.: An automated method for acquiring design knowledge from produce patents. Journal of Harbin Engineering University 30, 785–791 (2009) (in Chinese)
Yun, U.: Mining lossless closed frequent patterns with weight constraints. Knowledge Based Systems 20, 86–97 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yu, H., Guo, J., Shi, D., Chen, G., Cui, S. (2015). Knowledge Acquisition from Forestry Machinery Patent Based on the Algorithm for Closed Weighted Pattern Mining. In: Wang, H., et al. Intelligent Computation in Big Data Era. ICYCSEE 2015. Communications in Computer and Information Science, vol 503. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46248-5_39
Download citation
DOI: https://doi.org/10.1007/978-3-662-46248-5_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-46247-8
Online ISBN: 978-3-662-46248-5
eBook Packages: Computer ScienceComputer Science (R0)