Intuit, Inc.

Anshika Pandita

Govinda Sambamurthy

Manish Jain

Anand Patil

Satyajit Nath Bhowmik

Sirigiri Venkata Giri

Samar Ranjan

Charu Garg

Systems and methods for identifying recommended topics are disclosed. An example method may be performed by one or more processors of a system and include identifying one or more attributes of a system user, identifying a subset of topics relevant to the system user based on analyzing the one or more attributes of the system user using an analysis model trained with a machine learning process to identify relevant topics for system users based on historical user attributes, generating, for each respective topic of the subset of topics, using the trained analysis model, a relevance score for the respective topic based at least in part on a most recent system page previously accessed by the system user and a current system page accessed by the system user, and generating one or more recommended topics for the system user based on the relevance scores.

Method and system for providing personalized presearch for users of a data management system

A method and system provides personalized self-help assistance to users of a data management system. The method and system trains an analysis model to identify relevant assistance topics based personal attributes of the user and contextual attributes associated with the user. The method and system outputs personalized assistance topics recommendation data to the user based on the analysis of the analysis model.

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Bengaluru, India

Anshika Pandita