Monasterevin, Ireland

Jacek Adam Piskorski


Average Co-Inventor Count = 8.0

ph-index = 1


Company Filing History:


Years Active: 2024

where 'Filed Patents' based on already Granted Patents

1 patent (USPTO):

Title: Jacek Adam Piskorski: Innovator in Semantic Job Title Matching

Introduction

Jacek Adam Piskorski is a notable inventor based in Monasterevin, Ireland. He has made significant contributions to the field of semantic matching, particularly in the context of job titles. His innovative approach aims to enhance the accuracy and efficiency of job title matching through advanced methodologies.

Latest Patents

Jacek holds a patent for a method, computer system, and computer program product for semantic matching of job titles with limited contexts. This invention involves several key processes, including pre-processing and normalizing a job title. It also includes deconstructing the job title based on at least one semantic element. Furthermore, the invention encompasses training a machine learning model and creating a contextual word representation of the job title using the identified semantic elements. The final steps involve computing a similarity score for each semantic element and applying a weight to this score before making a final match assessment. Jacek's patent represents a significant advancement in the field of semantic technology.

Career Highlights

Jacek is currently employed at International Business Machines Corporation, commonly known as IBM. His work at IBM allows him to collaborate with leading experts in the field and contribute to innovative projects that leverage cutting-edge technology.

Collaborations

Some of Jacek's notable coworkers include Smitashree Choudhury and Stephen Mitchell. Their collaboration fosters a dynamic environment for innovation and problem-solving within the company.

Conclusion

Jacek Adam Piskorski's contributions to semantic matching technology exemplify the impact of innovative thinking in the tech industry. His work not only enhances job title matching but also showcases the potential of machine learning in improving various applications.

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