Refinitiv US Organization LLC

Other

Shai Hertz

Enav Weinreb

Oren Hazai

Yael Lindman

Mans Olof-Ors

Dmitry Levinson

Yehonatan Mataraso

Phani Nivarthi

Geoff Horrell

Ofri Rom

Hassan Malik

Jason E Rollins

Ellen Rotenberg

Evyatar Sharabi

Alexandra Rabinovich Goldshlager

Rani Shlivinski

Shai Taub

Yaniv Ben-Meir

Chen Weiss

Hila Zarosim

Danel Kotev

Lior Gelernter

Ehud Azikri

Saar Miron

Lior Weintraub

Savva Khalaman

Yossi Ben-Shlomo

Systems and techniques for determining relationships and association significance between entities are disclosed. The systems and techniques automatically identify supply chain relationships between companies based on unstructured text corpora. The system combines Machine Learning models to identify sentences mentioning supply chain between two companies (evidence), and an aggregation layer to take into account the evidence found and assign a confidence score to the relationship between companies.

Machine learning-based relationship association and related discovery and

Systems, technologies and techniques for generating a customized classification model are disclosed. The system and technologies, such as THOMSON REUTERS SELF-SERVICE CLASSIFICATION&#x2122;, employ part machine learning and part an user interactive approach to generate a customized classification model. The system combines a novel approach for text classification using a smaller initial set of data to initiate training, with a unique workflow and user interaction for customization.

Self-service classification system

The present disclosure is directed to methods, systems and programs for adjusting tagging of files. An illustrative method includes receiving a request to upload at least one document from a user via processor, assigning a first metadata tag via processor to at least one word contained within the at least one document, wherein the first metadata tag identifies the at least one word as an alias for a first unique entity, delivering the at least one document to the user including the first metadata tag via processor, receiving feedback via processor from the user relating to the assignment of the first metadata tag to the at least one word, determining at least one potential adjustment for the assignment of the first metadata tag via processor, sending information to the user proposing the at least one potential adjustment via processor, and receiving confirmation information from the user concerning the potential adjustment.

Apparatuses, methods and systems for adjusting tagging in a computing environment

Machine learning-based relationship association and related discovery and search engines

A multi-component software system facility matches unpublished academic manuscripts with a list or set of recommended potential 'best fit' publications, e.g., journals, e.g., those publications determined most likely to accept the manuscript for publication. Upon selecting from a set of recommended publications a user may electronically upload or submit or transmit the unpublished article or work or manuscript to a target publication review and editing system. The present invention provides a client or web-based interface to effectively integrate word processor and bibliographic management software and other resources, including third-party authority databases.

Systems, methods, and software for manuscript recommendations and submissions

Growing community of inventors

Tel Aviv, Israel

Shai Hertz