Workday, Inc.

Harikrishna Narayanan

Parag Avinash Namjoshi

Hamdi Jenzri

Yury Markovsky

Sergei Winitzki

Adam Charles Baker

Lakshminarayanan Renganarayana

Yunxing Zhang

Manjunath Balasubramaniam

Timothy Lee

Charles You

A document is received from a document provider. A representation of the document provider associated with the document within a document provider space is determined based at least in part on text boxes and corresponding coordinates associated with the text boxes within the document. The document provider associated with the document is determined based on a measure of similarity. A database is updated to associate the document with the determined document provider.

Utilizing machine learning to determine a document provider

A system for validating data includes an interface and a processor. The interface is configured to receive a data set. The processor is configured to calculate a data quality metric for the data set, wherein the data quality metric is based at least in part on a data distribution metric; determine a model to build based at least in part on the data quality metric; build the model; and provide the model for use.

Data validation for automatic model building and release

A system for improving a query response includes an interface and a processor. The interface is configured to receive a query. The processor is configured to determine a categorization for the query using a model. The categorization is associated with a confidence value. The processor is configured to a comparison of the confidence value and a first threshold, wherein the first threshold is determined to maximize a metric and modify the query response based at least in part on the categorization and the comparison.

Model validation for query intent

A secure tenant activity data system for a deployment service includes processor that is configured to decrypt a set of encrypted stream processed monitoring data to recover a set of stream processed monitoring data; determine a transaction identifier associated with the set of stream processed monitoring data; determine whether the transaction identifier has been seen associated with a set of previous data; in response to determining that the transaction identifier has been seen associated with the set of previous data, retrieve the set of previous data; decrypt the set of previous data to recover a set of decrypted previous data; aggregate the set of stream processed monitoring data with the set of decrypted previous data to generate a set of aggregated data; encrypt the set of aggregated data to create a set of encrypted aggregated data; and provide the set of encrypted aggregated data to a safe storage area.

User action collection for sensitive customer data

A secure tenant activity data system for a deployment service includes an interface and a processor. The interface is configured to receive a set of encrypted monitoring data collected and encrypted from a monitoring instrument from a tenant system. The processor is configured to decrypt the data for stream processing; encrypt and store the stream processed data; and provide the encrypted data with a tenant identifier to a deployment service. Steam processing is one or more of data cleaning, data rounding, data filtering, data smoothing, algorithmic processing, improving ranking of results, improved navigation, generating recommendations, generating metrics, or computation of features for a machine learning system.

A system for improving a query response includes an interface and a processor. The interface is configured to receive a query. The processor is configured to determine a categorization for the query using a model. The categorization is associated with a confidence value. The processor is configured to determine whether the confidence value is above a first threshold and, in response to the confidence value being above the first threshold, modify the query response based at least in part on the categorization.

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Alameda, CA, United States of America

Harikrishna Narayanan