基于图相似度的专利侵权检测方法研究
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摘要
[目的 /意义]针对如何准确进行专利侵权检测,提出一种基于图相似度的专利侵权检测方法。[方法/过程]将专利语义特征抽取为subject-action-object(SAO)结构并利用图论将其表示为图的形式,然后将图转换为邻接矩阵并计算邻接矩阵的相似性来完成专利侵权判定,最后利用专利样本数据比较该方法与传统方法的判定准确率。[结果 /结论]实证研究结果表明,本研究提出的方法判定准确率更高,比传统的基于专利文本向量的方法准确率提升4.89%,可以作为专利侵权检测的有效方法。
[Purpose/significance] Aimed at how to carry out patent infringement detection accurately,a patent infringement detection method based on graph similarity is proposed. [Method/process]The patent semantic feature is extracted into the Subject-Action-Object( SAO) structure and expressed as graph form by graph theory. Then the graph is transformed into adjacency matrix and the similarity of the adjacency matrix is calculated to complete the patent infringement judgment. Finally,it compare the accuracy of the method and the traditional method with the sample data. [Result/conclusion]The empirical results show that the proposed method is more accurate than the traditional method,and the accuracy rate is 4. 89% higher than that of the method based on patented text vector. So the method proposed in this study can be used as an effective method of patent infringement detection.
[Purpose/significance] Aimed at how to carry out patent infringement detection accurately,a patent infringement detection method based on graph similarity is proposed. [Method/process]The patent semantic feature is extracted into the Subject-Action-Object( SAO) structure and expressed as graph form by graph theory. Then the graph is transformed into adjacency matrix and the similarity of the adjacency matrix is calculated to complete the patent infringement judgment. Finally,it compare the accuracy of the method and the traditional method with the sample data. [Result/conclusion]The empirical results show that the proposed method is more accurate than the traditional method,and the accuracy rate is 4. 89% higher than that of the method based on patented text vector. So the method proposed in this study can be used as an effective method of patent infringement detection.
引文
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[26]CHOI S,PARK H,KANG D,et al.An SAO-based text mining approach to building a technology tree for technology planning[J].Expert systems with applications,2012,39(13):11443-11455.
[27]ZHANG M,ZHANG J,SU J,et al.A composite kernel to extract relations between entities with both flat and structured features[C]//Proceedings of the 21st international conference on computational linguistics and the 44th annual meeting of the Association for Computational Linguistics.Sydney:Association for Computational Linguistics,2006:825-832.
[28]李丽双,刘洋,黄德根.基于组合核的蛋白质交互关系抽取[J].中文信息学报,2013,27(1):86-92.
[29]MAGERMAN T,VAN LOOY B,SONG X.Exploring the feasibility and accuracy of latent semantic analysis based text mining techniques to detect similarity between patent documents and scientific publications[J].Scientometrics,2010,82(2):289-306.
[30]SHIBATA N,KAJIKAWA Y,SAKATA I.How to measure the semantic similarities between scientific papers and patents in order to discover uncommercialized research fronts:a case study of solar cells[C]//2010 Proceedings of PICMET'10.Phuket:Picmet Technology Management for Global Economic Growth,2010:1-6.
[31]彭继东,谭宗颖.一种基于文本挖掘的专利相似度测量方法及其应用[J].情报理论与实践,2010,33(12):114-118.
[32]陈芨熙,顾新建,陈国海,等.基于向量空间模型和专利文献特征的相似专利确定方法[J].浙江大学学报(工学版),2009,43(10):1848-1852.
[2]LANJOUW J O,SCHANKERMAN M.Characteristics of patent litigation:a window on competition[J].The rand journal of economics,2001,32(1):129-151.
[3]COHEN L,GURUN U G,KOMINERS S D.Patent trolls:evidence from targeted firms[EB/OL].[2017-05-06].https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2464303.
[4]REITZIG M,HENKEL J,SCHNEIDER F.Collateral damage for R&D manufacturers:how patent sharks operate in markets for technology[J].Industrial and corporate change,2010,19(3):947-967.
[5]GERMERAAD P B,MORRISON L.How avery dennison manages its intellectual assets[J].Research technology management,1998,41(6):36-43.
[6]张利.发明和实用新型专利侵权判定原则适用模型研究[C]//国家知识产权局条法司.专利法研究.北京:知识产权出版社,2006:306-328.
[7]徐兴祥.专利侵权判定研究[D].北京:中国政法大学,2011.
[8]SHIN J,PARK Y.Generation and application of patent claim map:text mining and network analysis[J].Journal of intellectual property rights,2005,10(3):198-205.
[9]STERNITZKE C,BARTKOWSKI A,SCHRAMM R.Visualizing patent statistics by means of social network analysis tools[J].World patent information,2008,30(2):115-131.
[10]KASRAVI K,RISOV M.Multivariate patent similarity detection[C]//Hawaii international conference on system sciences.Hawaii:IEEE,2009:1-8.
[11]SANTORO M D,BIERLY III P E,GOPALAKRISHNAN S,et al.Technological knowledge and governance in alliances among competitors[J].International journal of technology management,2007,38(1-2):69-89.
[12]PARK H,YOON J,KIM K.Identifying patent infringement using SAO based semantic technological similarities[J].Scientometrics,2012,90(2):515-529.
[13]LEE C,SONG B,PARK Y.How to assess patent infringement risks:a semantic patent claim analysis using dependency relationships[J].Technology analysis&strategic management,2013,25(1):23-38.
[14]INDUKURI K V,AMBEKAR A A,SUREKA A.Similarity analysis of patent claims using natural language processing techniques[C]//International conference on computational intelligence and multimedia applications.Sivakasi:IEEE,2007:169-175.
[15]马文姗.中文专利侵权检索模型研究[D].北京:北京工业大学,2012.
[16]武玉英,马羽翔,翟东升.基于SOM的中文专利侵权检测研究[J].情报杂志,2014(2):33-39.
[17]BERGMANN I,BUTZKE D,WALTER L,et al.Evaluating the risk of patent infringement by means of semantic patent analysis:the case of DNA chips[J].R&D management,2008,38(5):550-562.
[18]WILSON R J.Introduction to graph theory[M].Edinburgh:Pearson Education Limited,2015:260-275.
[19]CHARTRAND G,ZHANG P.A first course in graph theory[M].Boston:Mc Graw-Hill Higher Education,2013:26-49.
[20]BUNKE H.Graph matching:theoretical foundations,algorithms,and applications[EB/OL].[2017-08-15].http://www.ai.rug.nl/ki2/literature/graphmatch-bunke.pdf.
[21]MAYVAN B B,RASOOLZADEGAN A.Design pattern detection based on the graph theory[J].Knowledge-based systems,2017,120(15):211-225.
[22]CASCINI G,ZINI M.Measuring patent similarity by comparing inventions functional trees[M].Boston:Springer,2008:31-42.
[23]MOEHRLE M G,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.
[24]YOON J,KIM K.Detecting signals of new technological opportunities using semantic patent analysis and outlier detection[J].Scientometrics,2012,90(2):445-461.
[25]YOON J,PARK H,KIM K.Identifying technological competition trends for R&D planning using dynamic patent maps:SAO-based content analysis[J].Scientometrics,2013,94(1):313-331.
[26]CHOI S,PARK H,KANG D,et al.An SAO-based text mining approach to building a technology tree for technology planning[J].Expert systems with applications,2012,39(13):11443-11455.
[27]ZHANG M,ZHANG J,SU J,et al.A composite kernel to extract relations between entities with both flat and structured features[C]//Proceedings of the 21st international conference on computational linguistics and the 44th annual meeting of the Association for Computational Linguistics.Sydney:Association for Computational Linguistics,2006:825-832.
[28]李丽双,刘洋,黄德根.基于组合核的蛋白质交互关系抽取[J].中文信息学报,2013,27(1):86-92.
[29]MAGERMAN T,VAN LOOY B,SONG X.Exploring the feasibility and accuracy of latent semantic analysis based text mining techniques to detect similarity between patent documents and scientific publications[J].Scientometrics,2010,82(2):289-306.
[30]SHIBATA N,KAJIKAWA Y,SAKATA I.How to measure the semantic similarities between scientific papers and patents in order to discover uncommercialized research fronts:a case study of solar cells[C]//2010 Proceedings of PICMET'10.Phuket:Picmet Technology Management for Global Economic Growth,2010:1-6.
[31]彭继东,谭宗颖.一种基于文本挖掘的专利相似度测量方法及其应用[J].情报理论与实践,2010,33(12):114-118.
[32]陈芨熙,顾新建,陈国海,等.基于向量空间模型和专利文献特征的相似专利确定方法[J].浙江大学学报(工学版),2009,43(10):1848-1852.