Pearson Education, Inc.

John Behrens

Johann A Larusson

José Pablo González Brenes

Ilya Goldin

Jose Gonzalez-Brenes

Thomas McTavish

Jacob Anderson

Gennadiy Kukartsev

Yun Jin Rho

Yetian Chen

Yun Huang

Systems and methods for automatic generating of a Bayes net content graph are disclosed herein. The system can include a memory including a mapping matrix. The system can include at least one server. The at least one server can generate a user matrix having n columns and p rows. In some aspects, each of the n columns is associated with a student and each of the p rows is associated with a content item. The at least one server can: store the user matrix in the memory; retrieve the mapping matrix from the memory; iteratively identify prerequisite relationships between the skills identified in the user matrix; generate edges between the skills in the user matrix based on the iteratively identified prerequisite relationships; and orient the edges between the skill.

Methods for automatically generating Bayes nets using historical data

Systems and methods for simplifying data structuring in a database by applying a first content structure to interrelate a plurality of data packets and refining the interrelations based on data packet attributes are disclosed herein. The system can include a memory including: a structure database that can include a content structure including a plurality of content categories; and a content library database. The content library database can include a plurality of data packets. The system can include a server that can receive a plurality of data packets, organize the content according to the content structure, and update the organization of at least some of the data packets based on a determined attribute of those data packets.

Content database generation

Systems and methods for increasing data transmission rates through a content distribution network by generating a customized aggregation comprising data packets selected to maximize a data acceptance rate are disclosed herein. The system can include a memory including a content library database having a plurality of data packets and a user profile database. The system can further include a server that can: receive aggregation information identifying a set of delivery data packets and a set of assessment data packets; receive data packet data from the content library database; identify a recipient cohort; determine a recipient cohort lapsed time; generate an estimate of data packet transfer time for the aggregation; generate an updated aggregation based on the recipient cohort lapsed time and the estimate of data packet transfer time; and provide the updated aggregation to the user devices.

System and method for increasing data transmission rates through a content distribution network with customized aggregations

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Mishawaka, IN, United States of America

John Behrens