Text mining techniques for patent analysis

Information Processing and Management

Volumn 43, Issue 5, 2007, Pages 1216-1247

  Tseng, Yuen Hsien ^a   Lin, Chi Jen ^b   Lin, Yu I ^c  

^a NATIONAL TAIWAN NORMAL UNIVERSITY   (Taiwan)

^b WebGenie Information Ltd   (Taiwan)

^c UNIVERSITY OF TAIPEI   (Taiwan)

Author keywords

Clustering; Co word analysis; Phrase extraction; Summarization; Topic mapping

Indexed keywords

CLASSIFICATION (OF INFORMATION); CLUSTERING ALGORITHMS; FEATURE EXTRACTION; PATENTS AND INVENTIONS; TERMINOLOGY; TEXT PROCESSING;

CO-WORD ANALYSIS; KNOWLEDGE SHARING; PHRASE EXTRACTION; SUMMARIZATION; TOPIC MAPPING;

DATA MINING;

EID: 34247500870     PISSN: 03064573     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ipm.2006.11.011     Document Type: Article

References (72)

1. ACL-2003 Workshop on Patent Corpus Processing, 12 July 2003, Sapporo, Japan. http://www.slis.tsukuba.ac.jp/~fujii/acl2003ws.html.
2. ACM SIGIR 2000 Workshop on Patent Retrieval. http://research.nii.ac.jp/ntcir/sigir2000ws/.
3. Archibugi D., and Pianta M. Measuring technological change through patents and innovation survey. Technovation 16 9 (1996) 451-468
4. Bay, Y.-M. (2003). Development and applications of patent map in Korean high-tech industry. The first Asia-Pacific conference on patent maps, Taipei, October 29, pp. 3-23.
5. Be'de'carrax C., and Huot C. A new methodology for systematic exploitation of technology databases. Information Processing & Management 30 3 (1994) 407-418
6. Bekkerman, R., El-Yaniv, R., Winter, Y., & Tishby, N. (2001). On feature distributional clustering for text categorization. In Proceedings of the 24th annual international ACM-SIGIR conference on research and development in information retrieval, pp. 146-153.
7. Booker A., Condliff M., Greaves M., holt F.B., Kao A., Pierce D.J., et al. Visualizing text data sets. IEEE Computing in Science and Engineering 1 4 (1999) 26-34
8. Brown P.F., Della Pietra V.J., De Souza P.V., Mercer R.L., and Lai J.C. Class-based N-gram models of natural language. Computational Linguistics 18 4 (1992) 467-479
9. Campbell R.S. Patent trends as a technological forecasting tool. World Patent Information 5 3 (1983) 137-143
10. Chen, B. (1999). Introduction to patent map. Lecture notes for the training of patent mapping and patent analysis. Taipei, National Science Council (in Chinese).
11. Choueka, Y. (1988). Looking for needles in a haystack, or locating interesting collocational expressions in large textual databases. In Proceedings of the RIAO, pp. 609-623.
12. Deerwester S., Dumais S.T., Furnas G.W., Landauer T.K., and Harshman R. Indexing by latent semantic analysis. Journal of the American Society for Information Science 41 (1990) 391-407
13. Document Understanding Conferences. http://www-nlpir.nist.gov/projects/duc/.
14. Ernst H. Use of patent data for technological forecasting: the diffusion of CNC-technology in the machine tool industry. Small Business Economics 9 (1997) 361-381
15. Fagan J.L. The effectiveness of a nonsyntactic approach to automatic phrase indexing for document retrieval. Journal of the American Society for Information Science 40 2 (1989) 115-132
16. Fall C.J., Torcsvari A., Benzineb K., and Karetka G. Automated categorization in the international patent classification. ACM SIGIR Forum 37 1 (2003) 10-25
17. Fang, H., Tao, T., & Zhai, C. X. (2004). A formal study of information retrieval heuristics. In Proceedings of the 27th annual international ACM SIGIR conference on research and development in information retrieval, Sheffield, United Kingdom, pp. 49-56.
18. Fattori M., Pedrazzi G., and Turra R. Text mining applied to patent mapping: a practical business case. World Patent Information 25 (2003) 335-342
19. Fayyad U., Piatetsky-Shapiro G., Smyth P., and Uthurasamy R. Advances in knowledge discovery and data mining (1996), AAAI Press/The MIT Press
20. Frakes W.B., and Baeza-Yates R. Information retrieval: Data structure and algorithm (1992), Prentice Hall
21. Frank, E., Hall, M., & Trigg, L. Weka 3: Data Mining Software in Java. http://www.cs.waikato.ac.nz/ml/weka/.
22. Fujii, A., Iwayama, M., & Kando, N. (2004). Overview of patent retrieval task at NTCIR-4. In Proceedings of the fourth NTCIR workshop on evaluation of information retrieval, automatic text summarization and question answering, June 2-4, Tokyo, Japan.
23. Glenisson P., Glanzel W., Janssens F., and De Moor B. Combining full text and bibliometric information in mapping scientific disciplines. Information Processing & Management 41 6 (2005) 1548-1572
24. Hearst, M.A. (1999). Untangling text data mining. In Proceedings the 37th annual meeting of the association for computational linguistics, June 20-26, pp. 3-10.
25. Information Mapping Project. Computational Semantics Laboratory, Standford University. http://infomap.stanford.edu/.
26. Iwayama M., Fujii A., Kando N., and Marukawa Y. Evaluating patent retrieval in the third NTCIR workshop. Information Processing and Management 42 (2006) 207-221
27. Jain A.K., Murthy M.N., and Flynn P.J. Data clustering: a review. ACM Computing Reviews 31 3 (1999) 264-323
28. Joachims, T. (1998). Text categorization with support vector machines: learning with many relevant features. In Proceedings of the European conference on machine learning, Berlin, pp. 137-142.
29. Jung, S. (2003). Importance of using patent information. In WIPO-Most intermediate training course on practical intellectual property issues in business, organized by the World Intellectual Property Organization (WIPO), Geneva, November 10-14.
30. Karypis, G. CLUTO: a software package for clustering low- and high-dimensional datasets. http://www-users.cs.umn.edu/~karypis/cluto/.
31. Kim, J.-H., Huang, J.-X., Jung, H.-Y., & Choi, K.-S. (2005). Patent document retrieval and classification at KAIST. In Proceedings of the fifth NTCIR workshop on evaluation of information access technologies: information retrieval, question answering, and cross-lingual information access, Tokyo, Japan, December 6-9, pp. 304-311.
32. Kleiweg, P. Extended Kohonen maps. http://www.let.rug.nl/~kleiweg/kohonen/kohonen.html.
33. Kleiweg, P. Software for dialectometrics and cartography. http://www.let.rug.nl/~kleiweg/L04/.
34. Kohonen T. Self-organizing maps (1997), Springer-Verlag New York, Inc., Secaucus, NJ
35. Kruskal J.B. Multidimensional scaling and other methods for discovering structure. In: Enslein K., Ralston A., and Wilf H.S. (Eds). Statistical methods for digital computers (1977), Wiley, New York 296-339
36. Kupiec, J., Pedersen, J. O., & Chen, F. (1995). A trainable document summarizer. In Proceedings of the 18th international ACM SIGIR conference on research and development in information retrieval, pp. 68-73.
37. Lagus K., Kaski S., and Kohonen T. Mining massive document collections by the WEBSOM method. Information Sciences 163 1-3 (2004) 135-156
38. Lai K.-K., and Wu S.-J. Using the patent co-citation approach to establish a new patent classification system. Information Processing & Management 41 2 (2005) 313-330
39. Lamirel, J.-C., Shadi Al Shehabi, Hoffmann, M., & Francois, C. (2003). Intelligent patent analysis through the use of a neural network: experiment of multi-viewpoint analysis with the MultiSOM model. In Proceedings of the ACL workshop on patent corpus processing, Sapporo, Japan, 12 July.
40. Larkey, L. S. (1999). A patent search and classification system. In Proceedings the 4th ACM conference on digital libraries, pp. 179-187.
41. Lent, B., Agrawal, R., & Srikant, R. (1997). Discovering trends in text databases. In Proceedings of international conference on knowledge discovery and data mining, Newport Beach, California, USA, August 14-17.
42. Liu, S.-J. (2003). Patent map - a route to a strategic intelligence of industrial competitiveness. In The first Asia-Pacific conference on patent maps, October 29, Taipei, pp. 2-13.
43. Losiewicz P., Oard D.W., and Kostoff R.N. Textual data mining to support science and technology management. Journal of Intelligent Information Systems 15 2 (2000) 99-119
44. Mai, F.-D., Hwang, F., Chien, K.-m., Wang, Y.-M., & Chen, C.-y. (2002). Patent map and analysis of carbon nanotube. Science and Technology Information Center, National Science Council, ROC.
45. Mani I. Automatic summarization (2001), John Benjamins
46. Ng, H. T., Goh, W. B., & Low, K. L. (1997). Feature selection, perception learning, and a usability case study for text categorization. In Proceedings of the 20th international ACM-SIGIR conference on research and development in information retrieval, pp. 67-73.
47. Noyons, E. C. M., & Buter, R. K. CWTS Bibliometric Mapping Projects. http://www.cwts.nl/ed/projects/home.html.
48. Noyons, E. C. M., & van Raan, A. F. J. (1998a). Mapping scientometrics, informetrics, and bibliometrics. CWTS Working papers. http://www.cwts.nl/ed/sib/.
49. Noyons E.C.M., and van Raan A.F.J. Advanced mapping of science and technology. Scientometrics 41 (1998) 61-67
50. Porter M.F. An algorithm for suffix stripping. Program 14 3 (1980) 130-137
51. Robertson, S. E., & Walker, S. (1994). Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval. In Proceedings of the 17th annual international ACM SIGIR conference on research and development in information retrieval, Dublin, Ireland, July 03-06, pp. 232-241.
52. Salton G. Automatic text processing: The transformation, analysis, and retrieval of information by computer (1989), Addison-Wesley, MA
53. Schutze H. Word space. In: Hanson S.J., Cowan J.D., and Giles C.L. (Eds). Advances in neural information processing systems vol. 5 (1993), Morgan Kaufman 895-902
54. Sheremetyeva, S. (2003). Natural language analysis of patent claims. ACL workshop on patent corpus processing, Sapporo, Japan, 12 July.
55. Shinmori, A., Okumura, M., Marukawa, Y., & Iwayama, M. (2003). Patent claim processing for readability - structure analysis and term explanation. In ACL workshop on patent corpus processing, Sapporo, Japan, 12 July.
56. Singhal, A., Buckley, C., & Mitra, M. (1996). Pivoted document length normalization. In Proceedings of the 19th annual international ACM SIGIR conference on research and development in information retrieval, Zurich, Switzerland, pp. 21-29.
57. Smadja F. Retrieving collocations from text: Xtract. Computational Linguistics 19 (1993) 143-177
58. The 8th Science and Technology Foresight Survey - Study on Rapidly-Developing Research Areas - Interim Report, Science and Technology Foresight Center, National Institute of Science & Technology Policy, Japan, 2004. http://www.nistep.go.jp/index-e.html.
59. Tseng, Y.-H. (1999). Content-based retrieval for music collections. In Proceedings of the 22nd international ACM SIGIR conference on research and development in information retrieval, August 15-19, Berkeley, USA, pp. 176-182.
60. Tseng Y.-H. Automatic thesaurus generation for Chinese documents. Journal of the American Society for Information Science and Technology 53 13 (2002) 1130-1138
61. Tseng, Y.-H., Juang, D.-W. (2003). Document-self expansion for text categorization. In Proceedings of the 26th international ACM SIGIR conference on research and development in information retrieval, pp. 399-400.
62. Tseng, Y.-H., Juang, D.-W., & Chen, S.-H. (2004). Global and local term expansion for text retrieval. In Proceedings of the fourth NTCIR workshop on evaluation of information retrieval, automatic text summarization and question answering, June 2-4, Tokyo, Japan.
63. Tseng, Y.-H., Juang, D.-W., Wang, Y.-M., & Lin, C.-J. (2005). Text mining for patent map analysis. In Proceedings of IACIS Pacific 2005 conference, May 19-21, Taipei, Taiwan, pp. 1109-1116.
64. Uchida, H., Mano, A., & Yukawa, T. (2004). Patent map generation using concept-based vector space model. In Proceedings of the fourth NTCIR workshop on evaluation of information access technologies: information retrieval, question answering, and summarization, June 2-4, Tokyo, Japan.
65. United States Patent and Trademark Office. http://www.uspto.gov/.
66. van Rijsbergen, K. Information retrieval. http://www.dcs.gla.ac.uk/Keith/Chapter.2/Table_2.1.html.
67. WordNet: a lexical database for the English language, Cognitive Science Laboratory Princeton University. http://wordnet.princeton.edu/.
68. Yang, Y., Ault, T., Pierce, T., & Lattimer, C. W. (2000). Improving text categorization methods for event tracking. In Proceedings of the 23rd annual international ACM-SIGIR conference on research and development in information retrieval, pp. 65-72.
69. Yang, Y., Liu, X. (1999). A re-examination of text categorization methods. In Proceedings of the 22nd annual international ACM-SIGIR conference on research and development in information retrieval, pp. 42-49.
70. Yang, Y., Pedersen, J. (1997). A comparative study on feature selection in text categorization. In Proceedings of the international conference on machine learning, pp. 412-420.
71. Ye, J.-Y. (2004). Evaluation of term suggestion in an interactive Chinese retrieval system. Master Thesis, Department of Library and Information Science, Fu Jen Catholic University.
72. Yoon B., and Park Y. A text-mining-based patent network: analytical tool for high-technology trend. Journal of High Technology Management Research 15 (2004) 37-50