Morgan Stanley & Co. Incorporated

Ubs Business Solutions Ag

Omar Moustafa

Barry Scott Hurewitz

Vaughn Stephen Harvey

Scott Solomon

Thami Rachidi

Robert Treder

Hanoz Bhathena

Prashanth Jeganathen

Lauren Fleming

Methods and systems are described herein for improvements to identifying thematic relationships in data sets using machine learning models. In particular, the methods and systems describe a way to identify dynamic thematic relationships (e.g., thematic relationships that may change as a function of time) as a function of time.

Methods and systems for identifying dynamic thematic relationships as a function of time

Computer-based systems and methods that determine interest profiles of contacts of work product. The contact interest profiles may indicate the contacts' interests in particular topics of research work product and/or analyst teams within the research department that produced the research work product. The contacts' interest profiles may be determined based on research work product accessed by the contacts according to topic and/or analyst team that produced the research work product, the interaction of the contacts with the research department, and any other reliable information indicative of the contacts' topic and/or team interests. Also, research work product items produced by the entity may be rated for each contact based on, for example, the topic(s) of the research work product items and the analyst teams that produced the research work product items, as well as the contacts' topic and/or analyst team interests.

Computer-based systems and methods for determining interest levels of consumers in research work product produced by a research department

Computer-based systems and methods for computing a score (a 'target score') for the contacts of a research department. The target score may be computed for each contact for each analyst team of the research department. The target score indicates how resources should be deployed by the research department to maximize revenue for the research department. The target score is computed based on a number of metrics. These metrics can include both analyst-team-specific contact metrics that relate to the contact-analyst team combination, as well as account metrics that pertain to the investment accounts associated with each of the contacts. Weights for the metrics may be determined using an optimization algorithm.

Computer-based systems and method for computing a score for contacts of a financial services firm indicative of resources to be deployed by the financial services firm for the contacts to maximize revenue for the financial services firm

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Brooklyn, NY, United States of America

Omar Moustafa