Abstract
This paper analyzes technological evolution from viewpoint of change in technology system. As knowledge base, which used to describe technology system conventionally, suffers from heavy dependency on domain experts, this paper replaces knowledge base with hierarchical topic model to analyze the evolution process of technology system. Specifically, we find frequent closed itemsets from terminologies in patent documents at first, then discover association rules and use them to measure the importance of terminologies and semantic relationship between terminologies, afterwards we clean terminologies in corpus and run HLDA model to describe technology system, finally, we analyze technological evolution via changes of technology system. An empirical research on Hard disk drive demonstrates the feasibility of this method.
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References
Benson, C., Magee, C.: Quantitative determination of technological improvement from patent data. PLoS ONE 10(4), E0121635 (2013)
Dewulf, S.: Directed variation of properties for new or improved function product DNA, a base for connect and develop. Procedia Eng. 9, 646–652 (2011)
Yoon, J., Kim, K.: Trendperceptor: a property-function based technology intelligence system for identifying technology trends from patents. Expert Syst. Appl. 39(3), 2927–2938 (2012)
Moehrle, M., Walter, L., Geritz, A., et al.: Patent-based inventor profiles as a basis for human resource decisions in research and development. R&D Manage. 35(5), 513–524 (2005)
Choi, S., Kang, D., Lim, J., et al.: A fact-oriented ontological approach to SAO-based function modeling of patents for implementing function-based technology database. Expert Syst. Appl. 39(10), 9129–9140 (2012)
Yoon, J., Ko, N., Kim, J.: A function-based knowledge base for technology intelligence. Ind. Eng. Manage. Syst. 14(1), 73–87 (2015)
Wang, X., Qiu, P., Zhu, D., et al.: Indentification of technology development trends based on subject-action-object analysis the case of dye-sensitized solar cells. Technol. Forecast. Soc. Chang. 98, 24–46 (2015)
Choi, S., Kim, H., Yoon, J., et al.: An SAO-based text-mining approach for technology roadmapping using patent information. R&D Manage. 43(1), 52–73 (2013)
Choi, S., Park, H., Kang, D., et al.: An SAO based text mining approach to building a technology tree for technology planning. Exp. Syst. Appl. 39(13), 11443–11455 (2012)
Park, H., Yoon, J., Kim, K.: Identifying patent infringement using SAO based semantic technological similarities. Scientometrics 90(2), 515–529 (2012)
Blei, D.M., Griffiths, T., Jordan, M.I.: Hierarchical topic models and the nested Chinese Restaurant process. In: Sebastian, T., Lawrence, K., Bernhard, S. (eds.) Advances in Neural Information Processing Systems, Cambridge, MA. MIT press (2004)
Blei, D.M., Andrew, N., Jordan, M.I.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3, 993–1022 (2003)
Chen, L., Tokuda, N., Adachi, H.: A patent documents retrieval system addressing both semantic and syntactic properties [EB/OL], 15 Februrary 2016. http://www.aclweb.org/anthology/W03-2001
Frantzi, K., Sophia, A., Hideki, M.: Automatic recognition of multi-word terms: the C-value/NC-value method. Nat. Lang. Process. Digit. Libr. 3(2), 115–130 (2000)
Matsuo, Y., Ishizuka, M.: Keyword extraction from a single document using word co-occurrence statistical information. Int. J. Artif. Intell. Tools 13(1), 157–169 (2004)
Milios, E., Zhang, Y., He, B., et al.: Automatic term extraction and document similarity in special text corpora. In: Proceedings of the 6th Conference of the Pacific Association for Computational Linguistics, Halifax, Scotia N, Canada, pp. 275–284 (2003)
Pasquier, N., Bastide, Y., Taouil, R., et al.: Discovering frequent closed Itemsets for association rules [EB/OL], 14 Feburary 2016. http://hal.archives-ouvertes.fr/docs/00/46/77/47/PDF/Discovering_frequent_closed_itemsets_for_association_rules_Pasquier_et_al._ICDT_1999.pdf
Chen, L., Zhang, Z.Q., Shang, W.J.: Research method of technological evolution based on frequent closed itemset mining. Lib. Inf. Serv. 57(9), 107–111 (2013)
Chen, L., Zhang, Z.Q.: A method of recognizing technological architecture component based on patent documents. Lib. Inf. Serv. 58(10), 134–144 (2014)
McCallum, K.: MALLET: a machine learning for language toolkit [EB/OL]. http://people.cs.umass.edu/~mccallum/mallet/
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Chen, L., Lei, X., Yang, G., Zhang, J. (2017). Research on Method of Technological Evolution Analysis Based on HLDA. In: Park, J., Chen, SC., Raymond Choo, KK. (eds) Advanced Multimedia and Ubiquitous Engineering. FutureTech MUE 2017 2017. Lecture Notes in Electrical Engineering, vol 448. Springer, Singapore. https://doi.org/10.1007/978-981-10-5041-1_54
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DOI: https://doi.org/10.1007/978-981-10-5041-1_54
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