ABSTRACT
Patent litigation not only covers legal and technical issues, it is also a key consideration for managers of high-technology (high-tech) companies when making strategic decisions. Patent litigation influences the market value of high-tech companies. However, this raises unique challenges. To this end, in this paper, we develop a novel recommendation framework to solve the problem of litigation risk prediction. We will introduce a specific type of patent-related litigation, that is, Section 337 investigations, which prohibit all acts of unfair competition, or any unfair trade practices, when exporting products to the United States. To build this recommendation framework, we collect and exploit a large amount of published information related to almost all Section 337 investigation cases. This study has two aims: (1) to predict the litigation risk in a specific industry category for high-tech companies and (2) to predict the litigation risk from competitors for high-tech companies. These aims can be achieved by mining historical investigation cases and related patents. Specifically, we propose two methods to meet the needs of both aims: a proximal slope one predictor and a time-aware predictor. Several factors are considered in the proposed methods, including the litigation risk if a company wants to enter a new market and the risk that a potential competitor would file a lawsuit against the new entrant. Comparative experiments using real-world data demonstrate that the proposed methods outperform several baselines with a significant margin.
Supplemental Material
- S. Bashir and A. Rauber. Improving retrievability of patents in prior-art search. In Advances in Information Retrieval, pages 457--470. Springer, 2010. Google ScholarDigital Library
- Y. Cao, J. Fan, and G. Li. A user-friendly patent search paradigm. Knowledge and Data Engineering, IEEE Transactions on, 25(6):1439--1443, 2013. Google ScholarDigital Library
- C. V. Chien. Patent assertion and startup innovation. New America Foundation, Open Technology Institute White Paper, 2013.Google Scholar
- M. A. Hasan, W. S. Spangler, T. Griffin, and A. Alba. Coa: Finding novel patents through text analysis. In Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 1175--1184. ACM, 2009. Google ScholarDigital Library
- B. Jin, Y. Ge, H. Zhu, L. Guo, H. Xiong, and C. Zhang. Technology prospecting for high tech companies through patent mining. In Data Mining (ICDM), 2014 IEEE International Conference on, pages 220--229. IEEE, 2014. Google ScholarDigital Library
- X. Jin, S. Spangler, Y. Chen, K. Cai, R. Ma, L. Zhang, X. Wu, and J. Han. Patent maintenance recommendation with patent information network model. In Data Mining (ICDM), 2011 IEEE 11th International Conference on, pages 280--289. IEEE, 2011. Google ScholarDigital Library
- Y. Koren. Collaborative filtering with temporal dynamics. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '09, pages 447--456, New York, NY, USA, 2009. ACM. Google ScholarDigital Library
- J. O. Lanjouw and M. Schankerman. Characteristics of patent litigation: a window on competition. RAND journal of economics, pages 129--151, 2001.Google Scholar
- D. Lemire and A. Maclachlan. Slope one predictors for online rating-based collaborative filtering. In SDM, volume 5, pages 1--5. SIAM, 2005.Google ScholarCross Ref
- J. Lerner and A. Seru. The use and misuse of patent data: Issues for corporate finance and beyond. Booth/Harvard Business School Working Paper, 2015.Google Scholar
- P. Lopez, L. Romary, et al. Experiments with citation mining and key-term extraction for prior art search. In CLEF 2010-Conference on Multilingual and Multimodal Information Access Evaluation, 2010.Google Scholar
- B. J. Love. An empirical study of patent litigation timing: Could a patent term reduction decimate trolls without harming innovators? University of Pennsylvania Law Review, 161:1309, 2013.Google Scholar
- T. J. Lybbert and N. J. Zolas. Getting patents and economic data to speak to each other: An 'algorithmic links with probabilities' approach for joint analyses of patenting and economic activity. Research Policy, 43(3):530--542, 2014.Google ScholarCross Ref
- W. Magdy and G. J. Jones. Applying the kiss principle for the clef-ip 2010 prior art candidate patent search task. 2010.Google Scholar
- W. Magdy, P. Lopez, and G. J. Jones. Simple vs. sophisticated approaches for patent prior-art search. In Advances in Information Retrieval, pages 725--728. Springer, 2011. Google ScholarDigital Library
- S. Oh, Z. Lei, W.-C. Lee, P. Mitra, and J. Yen. Cv-pcr: a context-guided value-driven framework for patent citation recommendation. In Proceedings of the 22nd ACM international conference on Conference on information & knowledge management, pages 2291--2296. ACM, 2013. Google ScholarDigital Library
- J. Tang, B. Wang, Y. Yang, P. Hu, Y. Zhao, X. Yan, B. Gao, M. Huang, P. Xu, W. Li, et al. Patentminer: topic-driven patent analysis and mining. In Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 1366--1374. ACM, 2012. Google ScholarDigital Library
- S. Wu, J. Sun, and J. Tang. Patent partner recommendation in enterprise social networks. In Proceedings of the sixth ACM international conference on Web search and data mining, pages 43--52. ACM, 2013. Google ScholarDigital Library
Index Terms
- Minimizing Legal Exposure of High-Tech Companies through Collaborative Filtering Methods
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