Jason M Eisner

Title: Innovations by Inventor Jason M. Eisner

Introduction

Jason M. Eisner is a notable inventor based in Philadelphia, PA, with a significant portfolio of six patents. His contributions primarily focus on leveraging advanced techniques in natural language processing and secure data exchange systems. Eisner's innovative solutions have applications in finance and data security, marking him as a key figure in these domains.

Latest Patents

One of Eisner's latest patents is titled "Stock Market Prediction Using Natural Language Processing." This invention provides a method for utilizing NLP techniques to analyze online news feeds. The system extracts pertinent information to predict changes in stock prices or volatilities. It enables the creation of profitable trading strategies by recognizing company names and automatically filling simple templates that describe corporate actions. These templates can be clustered into groups correlated with stock price changes. The system comprises two main components: a message understanding component and a statistical correlation component, both designed to assess correlations between identified patterns and stock price fluctuations. Additionally, this method can be applied to a diverse range of text sources, including articles from the Wall Street Journal, financial newsletters, and annual reports. An enhanced version of the system also incorporates statistical patterns from Internet usage data and newly released texts on web pages.

Another significant invention by Eisner is a "Secure Data Interchange." This system governs the exchange of personal data between two parties, mediated by a secure intermediate party. Each participant maintains disclosure policies that dictate how their data can be shared, ensuring confidentiality and control over personal information dissemination.

Career Highlights

Throughout his career, Jason M. Eisner has held positions at various companies, including Pinpoint, Incorporated, where he further developed his expertise and innovative practices. His work has significantly impacted how industries utilize natural language processing and secure data sharing.

Collaborations

Eisner has collaborated with distinguished peers in his field, including notable individuals such as Lyle H. Ungar and Frederick S. Herz. These partnerships have contributed to enhancing his innovative projects and expanding the applicability of his inventions.

Conclusion

Jason M. Eisner exemplifies a forward-thinking inventor whose patents in natural language processing and secure data exchange have the potential to transform industries. His latest innovations not only address current challenges in stock market predictions and data security but also pave the way for future advancements in these crucial areas. As technology continues to evolve, Eisner's contributions will undoubtedly remain influential in shaping how we interact with data and make informed decisions.