[目的/意义] 采用hLDA从专利语料库中抽取层次主题，以描述隐藏在专利文本中的技术结构，并基于层次主题随时间变化情况进行技术演化分析。[方法/过程] 从专利术语中获取闭频繁项集，并基于此建立关联规则网络来度量术语的重要性和术语间语义关系强弱，进而对语料库进行重构，并对不同时间片段的专利集合进行层次主题结构抽取。[结果/结论] 将本方法应用于硬盘驱动器磁头领域的专利数据分析，实证结果表明该方法是一种可行和有效的技术演化分析方法。
[Purpose/significance] This paper proposes a method to analyze technological evolution based on technological structure extracted from patents' abstract.[Method/process] This paperappliesassociation rules algorithm to recognize significant terms in patent abstracts. Then,based on these terms itreconstructs corpus and runshLDA model to extract technological structure.[Result/conclusion] Finally, it analyzes technological evolution via changes of technological structure.An empirical research on Hard disk drive demonstrates the feasibility of this method.
[1] 何玉柱,张元哲,刘康,等.智能问答技术[J].中国人工智能学会通讯,2016,6(1):1-12.
[2] GRUBER T R.Toward principles for design of ontologies used for knowledge sharing?[J].International journal of human-computer studies,1995,43(5/6):907-928.
[3] 陶然,李晓菲.基于领域本体对专利情报知识的浅析[J]. 情报学报, 2008, 27(2):212-217.
[4] WANG X,QIU P,ZHU D,etal.Indentification of technology development trends based on subject-action-object analysis:the case of dye-sensitized solar cells[J].Technological forecasting & social change,2015,98:24-46.
[5] YOON J,KON,KIM J.A function-based knowledge base for technology intelligence[J].Industrial engineering & management systems,2015,14(1):73-87.
[6] CHOI S,KIM H,YOON J,et al.An SAO-based text-mining approach for technology roadmapping using patent information[J].R&D management,2013,43(1):52-73.
[7] DEWULF S.Directed variation of properties for new or improved function product DNA,a base for connect and develop[J].Procedia Engineering,2011,9:646-652.
[8] YOON J,KIM K.Trendperceptor:a property-function based technology intelligence system for identifying technology trends from patents[J].Expert system with application,2012,39(3):2927-2938.
[9] MOEHRLE M,WALTER L, GERITZ A,et al.Patent-based inventor profiles as a basis for human resource decisions in research and development[J].R&D management,2005,35(5):513-524.
[10] CHOI S,KANGD,LIM J,et al.A fact-oriented ontological approach to SAO-based function modeling of patents for implementing function-based technology database[J]. Expert system with application,2012,39(10):9129-9140.
[11] CHOI S,PARK H,KANG D,et al.An SAO based text mining approach to building a technology tree for technology planning[J].Expert system with application,2012,39(13):11443-11455.
[12] PARK H,YOON J,KIM K.Identifying patent infringement using SAO based semantic technological similarities[J].Scientometrics,2012,90(2):515-529.
[13] BLEI D M,GRIFFITHST,JORDAN M I,et al.Hierarchical topic models and the nested Chinese Restaurant process[EB/OL].[2016-02-12].http://machinelearning.wustl.edu/mlpapers/paper_files/NIPS2003_AA03.pdf.
[14] BLEI D M, ANDREWN,JORDAN M I.Latent Dirichlet allocation[J].Journal of machine learning research,2003(3):993-1022.
[15] FRANTZI K,SOPHIA A,HIDEKI M.Automatic recognition of multi-word terms:the C-value/NC-value method[J].International journal on digital libraries,2000,3(2):115-130.
[16] MATSUO Y,ISHIZUKA M.Keyword extraction from a single document using word co-occurrence statistical information[J].International journal on artificail intelligence tools,2011,13(1):157-169.
[17] BLEI D M,LAFFERTY J D.Visualizing Topics with multi-word expressions[EB/OL].[2016-12-27].https://arxiv.org/pdf/0907.1013v1.pdf.
[18] 陈亮,张静,杨冠灿,等. 基于专利文本的闭频繁项集在技术演化分析中的应用[J]. 图书情报工作, 2016,60(6):70-76.
[19] 陈亮,张志强,尚玮姣. 基于闭频繁项集挖掘的技术演化研究方法[J]. 图书情报工作, 2013, 57(19):107-111.
[20] PASQUIER N,BASTIDE Y,TAOUIL R,et al.Discovering frequent closed Itemsets for association rules[EB/OL].[2016-02-12].http://hal.archives-ouvertes.fr/docs/00/46/77/47/PDF/Discovering_frequent_closed_itemsets_for_association_rules_Pasquier_et_al._ICDT_1999.pdf.
[21] McCALLUM K.MALLE T:a machine learning for language toolkit[EB/OL].[2016-02-12].http://people.cs.umass.edu/~mccallum/mallet/.
