Baruipur, India

Tapashi Mandal

USPTO Granted Patents = 5 

Average Co-Inventor Count = 5.0

ph-index = 3

Forward Citations = 206(Granted Patents)


Company Filing History:


Years Active: 2019-2022

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5 patents (USPTO):Explore Patents

Title: Tapashi Mandal: Innovator in Data Extraction and Abbreviation Disambiguation

Introduction

Tapashi Mandal is a prominent inventor based in Baruipur, India. She has made significant contributions to the fields of data extraction and machine learning. With a total of five patents to her name, her work focuses on innovative methods that enhance the processing and understanding of data.

Latest Patents

One of her latest patents is titled "Method and system for extracting entity information from target data." This invention discloses a method and system that refines target data to obtain base entity information using a predefined algorithm. The process involves generating strings for each base entity, sorting them, identifying entity types based on ontology, and mapping them to obtain comprehensive entity information.

Another notable patent is "System and method for context-based abbreviation disambiguation using machine learning on synonyms of abbreviation expansions." This system comprises an ontological databank and a server arrangement that processes text with abbreviations. It calculates various match scores to determine valid expansions for target abbreviations, enhancing the clarity and understanding of abbreviated terms in context.

Career Highlights

Tapashi Mandal currently works at Innoplexus AG, where she continues to innovate and develop her ideas. Her work has garnered attention for its practical applications in data processing and machine learning.

Collaborations

Some of her coworkers include Vatsal Agarwal and Gaurav Tripathi, who contribute to the collaborative environment at Innoplexus AG.

Conclusion

Tapashi Mandal is a trailblazer in her field, with a focus on improving data extraction and abbreviation disambiguation through her innovative patents. Her contributions are paving the way for advancements in data processing technologies.

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