Abstract
This research defines the current gap between big data analytics and patent litigation. It discovers how big data analytics can be applied to the patent industry in order to create more effective risk analysis, an early warning system, and preventative strategies for inside and outside of the courtroom. Big data has the potential to modify current practices in the patent industry, namely geared towards aiding patent examiners, attorneys, inventors, jurors, and judges. It also offers a solution to the threat that patent monetizers pose on smaller companies and inventors, who often lose rights to their patents and other assets in these sometimes unavoidable lawsuits. This research examines the application of big data in the healthcare industry for real-time results and preventative measures. These actions set a good precedent for further diffusion into other industries, specifically patent legal. Features for future implementation and project development are presented as a roadmap to create a universal big data analytics system for the patent industry. Finally, this research will touch upon a case study of Apple v. Samsung and identify how the case might have yielded different results in the event that big data analytics had been applied to the legal proceedings
Keywords
Big Data; Analytics; Litigation; Law; Health Care; Patent; Computer Science
Document Type
Thesis
Year of Completion
2016
Advisor
Dr. Brian Galli
Academic Department
Computer Science
Recommended Citation
Margulis, Chloé, "The Application of Big Data Analytics to Patent Litigation" (2016). Undergraduate Honors College Theses 2016-. 5.
https://digitalcommons.liu.edu/post_honors_theses/5