A literature review on the state-of-the-art in patent analysis

World Patent Information

Volumn 37, Issue , 2014, Pages 3-13

  Abbas, Assad ^a   Zhang, Limin ^a   Khan, Samee U ^a  

^a NORTH DAKOTA STATE UNIVERSITY   (United States)

Author keywords

Natural language processing; Patent analysis; Text mining; Visualization techniques

Indexed keywords

EID: 84900511122     PISSN: 01722190     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.wpi.2013.12.006     Document Type: Review

References (61)

1. Bonino D., Ciaramella A., Corno F. Review of the state-of-the-art in patent information and forthcoming evolutions in intelligent patent informatics. World Pat Inf 2010, 32(1):30-38.
2. Hunt D., Nguyen L., Rodgers M. Patent searching: tools and techniques 2007, John Wiley and Sons.
3. Liu S.H., Liao H.L., Pi S.M., Hu J.W. Development of a patent retrieval and analysis platform-a hybrid approach. Expert Syst Appl 2011, 38(6):7864-7868.
4. Saad F., Nürnberger A. Overview of prior-art cross-lingual information retrieval approaches. World Pat Inf 2012, 304-314.
5. The United States Patent and Trademark Office. [accessed 28.03.13]. http://www.uspto.gov/.
6. European Patent Office. [accessed 28.04.13]. http://www.epo.org/.
7. Japan Patent Office. [accessed 28.03.13]. http://www.jpo.go.jp/.
8. Yoon B., Park Y. A text-mining-based patent network: analytical tool for high-technology trend. J High Technol Manag Res 2004, 15:37-50.
9. Kostoff R. The use and misuse of citation analysis in research evaluation. Scientometrics 1998, 43(1):27-43.
10. Tseng Y.H., Lin C.J., Lin Y.I. Text mining techniques for patent analysis. Inform Process Manag 2007, 43(5):1216-1247.
11. Ernst H. Patent information for strategic technology management. World Pat Inf 2003, 25(3):233-242.
12. Hufker T., Alpert F. Patents: a managerial perspective. J Prod Brand Manag 1994, 3(4):44-54.
13. Abraham B.P., Moitra S.D. Innovation assessment through patent analysis. Technovation 2001, 21(4):245-252.
14. Lee C., Song B., Park Y. How to assess patent infringement risks: a semantic patent claim analysis using dependency relationships. Technol Anal Strat Manag 2013, 25(1):23-38.
15. Sternitzke C., Bartkowski A., Schramm R. Visualizing patent statistics by means of social network analysis tools. World Pat Inf 2008, 30:115-131.
16. Witten IH. Text mining., [accessed 09.10.13]. http://www.cs.waikato.ac.nz/%7Eihw/papers/04-IHW-Textmining.pdf.
17. Yoon J., Park H., Kim K. Identifying technological competition trends for R&D planning using dynamic patent maps: SAO-based content analysis. Scientometrics 2013, 1-19.
18. Chang P.L., Wu C.C., Leu H.J. Using patent analyses to monitor the technological trends in an emerging field of technology: a case of carbon nanotube field emission display. Scientometrics 2010, 82(1):5-19.
19. Phaal R., Farrukh C.J.P., Mills J.F., Probert D.R. Customizing the technology roadmapping approach. Manag Eng Technol 2003, 361-369.
20. Trappey A.J.C., Trappey C.V., Wu C.-Y.W., Fan C.Y., Lin Y.-L. Intelligent patent recommendation system for Innovative design collaboration. J Netw Comput Appl 2013, 36:1441-1450.
21. Du R., Ai S. Cross-organizational knowledge acquisition through flexible Hiring and joint R&D: insights from a survey in China. Expert Syst Appl 2008, 35:434-441.
22. Park H., Ree J.J., Kim K. Identification of promising patents for technology transfers using TRIZ evolution trends. Expert Syst Appl 2013, 736-743.
23. Shih M.J., Liu D.R., Hsu M.L. Discovering competitive intelligence by mining changes in patent trends. Expert Syst Appl 2010, 37(4):2882-2890.
24. Kim Y.G., Suh J.H., Park S.C. Visualization of patent analysis for emerging technology. Expert Syst Appl 2008, 34(3):1804-1812.
25. Yu W.D., Lo S.S. Patent analysis-based fuzzy inference system for technological strategy planning. Automat Constr 2009, 18(6):770-776.
26. Wang W.M., Cheung C.F. A semantic-based intellectual property management system (SIPMS) for supporting patent analysis. Eng Appl Artif Intell 2011, 24(8):1510-1520.
27. Park H., Kim K., Choi S., Yoon J. A patent intelligence system for strategic technology planning. Expert Syst Appl 2013, 2373-2390.
28. Taduri S., Lau G.T., Law K.H., Yu Hang, Kesan J.P. Developing an ontology for the US patent system. In Proceedings of the 12th Annual International Digital Government Research Conference: Digital Government Innovation in Challenging Times 2011, 157-166.
29. Taduri S, Lau GT, Law KH, Hang Yu, Kesan JP. A patent system ontology for facilitating retrieval of patent related information., [accessed 12.04.13]. http://eil.stanford.edu/publications/sid/icegov_2012.pdf.
30. Shih M.J., Liu D.R. Patent classification using ontology-based patent network analysis. Pacific Asia Conference on Information Systems, Taiwan 2010, 962-972.
31. Segev A., Kantola J. Identification of trends from patents using self-organizing maps. Expert Syst Appl 2012, 13235-13242.
32. Choi S., Park H., Kang D., Lee J.Y., Kim K. An SAO-based text mining approach to building a technology tree for technology planning. Expert Syst Appl October 2012, 11443-11455.
33. Park H., Yoon J., Kim K. Identifying patent infringement using SAO based semantic technological similarities. Scientometrics 2012, 90(2):515-529.
34. Sungchul C., Kim H., Yoon J., Kim K., Lee J.Y. An SAO-based text-mining approach for technology roadmapping using patent information. R&D Manag 2013, 43(1):52-74.
35. Yoon J., Kim K. TrendPerceptor: a property-function based technology intelligences system for identifying technology trends from patents. Expert Syst Appl 2012, 39(3):2927-2938.
36. Yoon J., Kim K. An analysis of property-function based patent networks for strategic R&D planning in fast-moving industries: the case of silicon-based thin film solar cells. Expert Syst Appl 2012, 7709-7717.
37. Tang J., Wang B., Yang Y., Hu P., Zhao Y., Yan X., et al. Patentminer: topic-driven patent analysis and mining. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2012, 1366-1374.
38. Ghazinoory S., Ameri F., Farnoodi S. An application of the text mining approach to select technology centers of excellence. Technol Forecast Soc Change 2012, 80:918-931.
39. Coussement K, Poel DVD. Integrating the voice of customers through call center emails into a decision support system for churn prediction. Inform Manag 45(3):164-74. doi:10.1016/j.im.2008.01.005.
40. Zanasi A. Virtual weapons for real wars: text mining for national security. Proceedings of the International Workshop on Computational Intelligence in Security for Information Systems CISIS'08 2009, 53-60. Springer Berlin Heidelberg.
41. Liu B., Zhang L. A survey of opinion mining and sentiment analysis. Mining text data 2012, 415-463.
42. Cohen KB, Hunter L. Getting started in text mining. PLoS Comput Biol 4(1):e20. PMC 2217579. PMID 18225946. doi:10.1371/journal.pcbi.0040020.
43. Yoon J., Kim K. Detecting signals of new technological opportunities using semantic patent analysis and outlier detection. Scientometrics 2011, 1-17.
44. Han J., Kamber M. Mining association rules in large databases. Data mining concepts and techniques 2001, Morgan Kaufmann, San Francisco, CA.
45. Kohonen T. Self-organization and associative memory 1988, Springer-Verlag, Berlin,German.
46. Lin C.T., Lee C.S.G. Neural-network-based fuzzy logic control and decision system. IEEE Trans Comput 1991, 40(12):1320-1336.
47. Dewulf S. Directed variation of properties for new or improved function product DNA-a base for connect and develop. Procedia Eng 2011, 9:646-652.
48. Gerken J.M., Moehrle M.G. A new instrument for technology monitoring: novelty in patents measured by semantic patent analysis. Scientometrics 2012, 91(3):645-670.
49. Segev A., Leshno M., Zviran M. Internet as a knowledge base for medical diagnostic assistance. Expert Syst Appl 2007, 33(1):251-255.
50. Che H.C., Lai Y.H., Wang S.Y. Assessment of patent legal value by regression and back-propagation neural network. Int J Syst Innovation 2009, 1:31-47.
51. Knowledgist, [accessed 21.05.13]. http://inventionmachine.com/default.aspx.
52. Masiakowski P., Wang S. Integration of software tools in patent analysis. World Pat Inf 2013, 35(2):97-104.
53. Gionis A., Mannila H., Mielikäinen T., Tsaparas P. Assessing data mining results via swap randomization. ACM Trans Knowl Discov Data (TKDD) 2007, 1(3):14.
54. Moehrle M.G., Walter L., Bergmann I., Bobe S., Skrzipale S. Patinformatics as a business process: a guideline through patent research tasks and tools. World Pat Inf 2010, 32(4):291-299.
55. Trippe A.J. Patinformatics: tasks to tools. World Pat Inf 2003, 25(3):211-221.
56. Barry K, Domb E, Michael S. TRIZ - what is TRIZ. The TRIZ, [accessed 29.10.13]. http://cmapspublic.ihmc.us/rid=1206064509716_727387479_10719/TRIZ%20-%20What%20Is%20TRIZ.pdf.
57. Verhaegen P.-A., D'hondt J., Vertommen J., Dewulf S., Duflou J.R. Relating properties and functions from patents to TRIZ trends. CIRP J Manuf Sci Technol 2009, 1(3):126-130.
58. Yoon J., Kim K. An automated method for identifying TRIZ evolution trends from patents. Expert Syst Appl 2011, 38(12):15540-15548.
59. Jain A.K., Murty M.N., Flynn P.J. Data clustering: a review. ACM Comput Surv (CSUR) 1999, 31(3):264-323.
60. Liu G. Visualization of patents and papers in terahertz technology: a comparative study. Scientometrics 2013, 94(3):1037-1056.
61. Hanbury A., Bhatti N., Lupu M., Mörzinger R. Patent image retrieval: a survey. Proceedings of the 4th ACM workshop on Patent information retrieval 2011, 3-8.