American Express Travel Related Services Company, Inc.

Dawn Thomas

Tirthankar Choudhuri

Lee C Chau

Subhajit Sanyal

Subhra Shankar Purkayastha

Kamal Gupta

Mohd Arshad Naeem

Vikas Grover

Ajay Choudhary

Amit Jagdish Agarwal

Pranav Mehta

Prakruthi Prabhakar

Shourya Roy

Salil Joshi

Bharath Venkatesh

Yue Jiao

The present disclosure presents systems and related methods for creating real-time predictions. One such method comprises receiving, by a computing device, a first set of data and a second set of data, wherein the first set of data comprises a plurality of items available from a first source for a first set of users and the second set of data comprises transaction purchase data for a second set of users that have reward accounts, utilizing a predictive data model that determines a propensity score for a user from only behavior data that is not attributed to the user; receiving a third set of data from a third source comprising social media channel data for a third set of users; and updating the predictive data model to determine the propensity score for the user based at least in part on the third set of data.

Systems and methods for tailoring marketing

Disclosed are various approaches for providing a natural language interface for searching databases. A natural language query is parsed to identify a plurality of tokens. At least one operator is identified with a machine-learning model based at least in part on the plurality of tokens. Next, at least one attribute and at least one respective attribute value are identified with a machine-learning model based at least in part on the plurality of tokens. Then, at least one constraint is identified with a machine-learning model based at least in part on the plurality of tokens. Finally, a machine language query is generated based at least in part on the at least one operator, the constraint(s), the attribute(s), and the respective attribute value(s).

Natural language interface to databases

The systems, methods and computer program products (collectively 'system') described herein relate to customized real time data delivery. The system may be configured to receive, by a performance marketing cluster, first data from a first data source. The system may also receive, by the performance marketing cluster, second data from a second data source. The system may determine, by the marketing cluster, an analysis scheme for the first data and the second data based on the first data source. The system may also determine, by the marketing cluster, at least one of a propensity to act or a recommendation selected from a predefined number of available options for a population based on the analysis scheme and the first data source.

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Kew Gardens, NY, United States of America

Dawn Thomas