Patent Classification Using Hybrid Classifier Systems

Abstract:

Patents are distributed through hundreds of collections, divided up by general area. A hybrid classifier system thus can be a powerful solution to difficult patent classification problems. In this study, we present a system for classifying patent documents on a hybrid approach by combining multiple text classifiers (Naïve Bayes, KNN and Rocchio). Decisions made by various text classifiers can be combined by voting and sampling mechanisms in the system. A prototype system was developed and tested in a real world task. The results have indicated that the accuracy of the hybrid approach is more stable than that of any of the three individual text classifiers.

• Periodical: Advanced Materials Research (Volume 187)
• Pages: 458-463
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.187.458
• Online since: February 2011
• Authors: Su Houn Liu, Hsiu Li Liao, Shih Ming Pi, Chih Chiang Kao
• Keywords: Patent, Patent Classification, Text Classifier

References

[1] F. A. Barros, E. F. A. Silva, R. B. C. Prudencio, V. M. Filho, A. C. A. Nascimento: Combining Text Classifiers and Hidden Markov Models for Information Extraction. International Journal on Articial Intelligence Tools. Vol. 18(2) (2009).

DOI: 10.1142/s0218213009000147

[2] P. Bennett, S. Dumais, E. Horvitz,: The Combination of Text Classifiers Using Reliability Indicators. Information Retrieval. Vol. 8, (2005), pp.67-100.

DOI: 10.1023/b:inrt.0000048491.59134.94

[3] Lee, C. H.: A Study of Apply-ing Data Mining Classification Techniques to Patent Analysis. Master Thesis, Chung-Yuan Univ. (2003).

[4] C. J. Fall, A. Torcsvari, K. Benzineb and G. Karetka: Automated Categorization in the International Patent Classification. ACM SIGIR Forum archive. Vol. 37(1), (2003) pp.10-25.

DOI: 10.1145/945546.945547

[5] A. K. Khalid, A. Tyrrel, A. Vachher and T. Travers: Combining Multiple Classifiers for Text Categorization. CIKM2001. (2001) pp.5-10.

[6] L. S. Larkey: A patent search and classification system. In Proceedings of DL-99, 4th ACM Conference on Digital Libraries. (1999) pp.179-187.

[7] L. S. Larkey and W. B. Croft: Combining classifiers in text categorization. Proceedings of SIGIR-96, 19th ACM International Conference on Research and Development in Information Retrieval. (1996) pp.289-297.

DOI: 10.1145/243199.243276

[8] S. Lee, H. Seol and Y. Park: Using patent information for designing new product and technology. R & D Management. Vol. 38(2), (2008) pp.169-181.

[9] T. Thorsten and M. A. Mittermayer: Text Mining for Technology. Monitoring IEEE IEMC (2002).

[10] Y. Tseng, C. Lin and Y. Lin: Text mining techniques for patent analysis. Information Processing & Management. Vol. 43(5), (2007) pp.12-16.

DOI: 10.1016/j.ipm.2006.11.011

[11] C. J. Van Rijsbergen: Information Retrieval. Butterworths, London (1979).

[12] Y. Yang and X. Liu: A re-examination of text categorization methods. SIGIR '99, Proceedings of the 22ndb Annual International ACM Conference on Research and Development in Information Retrieval. (1999) pp.42-49.

DOI: 10.1145/312624.312647