Company Filing History:
Years Active: 2024-2025
Title: Inbal Horev: Innovator in Textual Data Processing
Introduction
Inbal Horev is a notable inventor based in Tel Aviv, Israel. He has made significant contributions to the field of textual data processing, holding a total of four patents. His work focuses on developing systems and methods that enhance the efficiency and accuracy of topic modeling and classification in textual communications.
Latest Patents
Horev's latest patents include a "System and method for rapid initialization and transfer of topic models by a multi-stage approach." This innovative method involves applying a first stage topic model to textual data, which is trained to discover a plurality of topics and their corresponding word distributions. The process generates seeded words for specific topics based on selection rules and the discovered distributions, ultimately creating a second stage topic model for improved topic identification.
Another significant patent is the "System and method for generating a multi-label classifier for textual communications." This method trains multiple single-label classifiers to categorize textual data into predefined revenue-based labels. The multi-label classifier is then trained using the output from these single-label classifiers, allowing it to classify textual data into a vector of revenue-based labels along with their classification scores.
Career Highlights
Inbal Horev is currently employed at Gong I.O. Ltd., where he continues to innovate in the realm of textual data processing. His work has garnered attention for its practical applications in various industries, enhancing the way organizations analyze and interpret textual information.
Collaborations
Horev collaborates with talented individuals such as Omri Allouche and Raquel Sitman, who contribute to the dynamic environment of innovation at Gong I.O. Ltd. Their combined expertise fosters a culture of creativity and advancement in their projects.
Conclusion
Inbal Horev stands out as a prominent inventor in the field of textual data processing, with a focus on developing advanced systems for topic modeling and classification. His contributions are shaping the future of how textual data is analyzed and utilized across various sectors.