Capital One Services, LLC

Ricky Su

Scott Matthew Anderson

David Spencer Warren

Daniel Lantz

Shannon Hsu

Anirudha Simha

Remel Tucker

Alison Chi

Cosette Goldstein

Methods and systems are described herein for merging datasets from multiple content domains for training a prediction model to predict a solution for a request related to a specific content domain. A dataset for a content domain may include requests and solutions organized as groups. For example, a dataset for a first content domain may include a first group having (a) a first set of requests (e.g., questions or queries) related to a first topic, and (h) a solution (e.g., an answer) associated with the first set of requests. The datasets of different content domains are analyzed based on context-based vector representations of the requests or solutions to determine the groups that are similar and merge those similar groups into a single merged group. A prediction model is trained with the merged groups for obtaining a prediction of a solution to any given request.

Merging data from various content domains to train a machine learning model to generate predictions for a specific content domain

Systems, methods, and apparatuses are described for determining compliance with a plurality of restrictions associated with one or more devices in an organization. First text indicating restrictions may be received, and second text indicating a current configuration of one or more devices may be received. Both sets of text may be processed by, e.g., removing a portion of the text based on a predetermined list of terms and simplifying the text using a lemmatization algorithm. A first vector and second vector may be generated based on the processed sets of text, and each vector may be weighted based on an inverse frequency of words in their respective text. Each vector may be normalized based on semantic analysis. The two vectors may be compared. Based on the comparison, third text corresponding to a portion of the second vector may be generated and transmitted to a third computing device.

Device requirement and configuration analysis

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Richmond, VA, United States of America

Ricky Su