| CPC G06Q 30/0204 (2013.01) [G06N 20/00 (2019.01); G06Q 30/0201 (2013.01); G06Q 30/0276 (2013.01)] | 21 Claims |
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1. An apparatus, comprising:
one or more memory devices; and
one or more processing devices, in communication with the one or more memory devices, and configured to implement:
a subject module that receives subject data associated with a subject, the subject data comprising data that describes the subject;
an entity module that obtains external third party entity data from at least one online source and supplements the external third party entity data with domain-specific entity data comprising internal entity data to create a customized entity data set;
a training module that trains a machine learning model using the customized entity data set;
an affinity module that determines, using the machine learning model, an affinity level of each of one or more entities in relation to the subject, the subject data provided as input to the machine learning model, the machine learning model providing output for determining the affinity level based at least in part on a digital encoding of semantic similarity between an entity and the subject using text descriptions of the entity and the subject, the affinity level indicating the entity's likelihood of providing a response related to the subject;
a presentation module that:
generates an interactive graphical interface comprising graphical representations of one or more entities, the one or more entities divided into segmented groups within the graphical interface according to their affinity levels with the subject such that each entity within a segmentation group is indicated with a same graphical representation that is different from a graphical representation of a different segmentation group;
presents the interactive graphical interface on a display;
receives an input on one of the graphical representations of an entity within the graphical interface in response to detecting a user's interaction with the one of the graphical representations; and
dynamically presents metadata for an entity in response to receiving input on the graphical representation of the entity; and
a campaign module that generates one or more promotional campaign strategies for the subject based at least in part on the affinity level of each of the one or more entities in relation to the subject, the one or more promotional campaign strategies targeting the subject to the one or more entities,
wherein the entity module monitors for new entity data from the at least one online source and supplements the customized entity data set with new entity data that is available from the at least one online source, and
wherein the training module receives feedback associated with the one or more promotional campaign strategies and iteratively retrains the machine learning model using the received feedback and the supplemented customized entity data to refine the one or more promotional campaign strategies for the subject.
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