Tel Aviv, Israel

Tamar Lavee


Average Co-Inventor Count = 5.9

ph-index = 2

Forward Citations = 4(Granted Patents)


Company Filing History:


Years Active: 2013-2021

where 'Filed Patents' based on already Granted Patents

6 patents (USPTO):

Title: Tamar Lavee: Innovator in Automated Claim Detection and Argument Construction

Introduction

Tamar Lavee is a prominent inventor based in Tel Aviv, Israel. She has made significant contributions to the field of automated claim detection and argument construction. With a total of six patents to her name, Lavee is recognized for her innovative approaches to processing and analyzing content.

Latest Patents

Lavee's latest patents include methods for automatic detection of claims with respect to a topic and automatic construction of arguments. The first patent describes a method that utilizes at least one hardware processor to receive a topic under consideration and relevant content. It detects claims related to the topic by identifying boundaries within the content and outputs a list of these claims. The second patent outlines a method where a claim function is applied to mine content resources, extracting claims related to the topic. It also involves a classification function that assigns tags to the extracted claims, enhancing the organization and retrieval of information.

Career Highlights

Tamar Lavee is currently employed at International Business Machines Corporation (IBM), where she continues to develop her innovative ideas. Her work focuses on leveraging technology to improve the efficiency of information processing and argumentation.

Collaborations

Lavee collaborates with notable colleagues, including Ehud Aharoni and Dan Gutfreund. Their combined expertise contributes to the advancement of their projects and the overall success of their initiatives.

Conclusion

Tamar Lavee is a trailblazer in the realm of automated claim detection and argument construction. Her patents reflect her commitment to innovation and her ability to address complex challenges in content analysis.

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