| CPC G06Q 30/0185 (2013.01) [G06F 40/40 (2020.01); G06N 5/045 (2013.01); G06N 20/20 (2019.01); G06Q 30/014 (2013.01); G06Q 30/0282 (2013.01)] | 19 Claims |
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1. A system for retail product listing escalation event detection, the system comprises:
a network interface for accessing a wide-area network;
a user interface device; and
a control circuit coupled to the network interface and the user interface device, the control circuit executes computer-readable instructions to:
aggregate a plurality of content items from the wide-area network from a plurality of online resources, including social media services, wherein the plurality of content items comprises social media content;
determine a topic classification of a content item based on a first machine learning (ML) model;
determine an escalation classification of the content item based on a second ML model;
generate, with an ML explanation engine, a keyword list comprising a plurality of keywords from the content item and scores associated with each of the plurality of keywords based on the topic classification from the first ML model and the escalation classification from the second ML model;
select, with a keyword analysis module, a list of top keywords based on performing a keyword frequency analysis on a plurality of keyword lists associated with the plurality of content items, including a plurality of social media content items; and
provide for display, via the user interface device, an escalation event detected by the second ML model, a topic associated with the escalation event detected by the first ML model, and one or more keywords associated with the topic determined based on the list of top keywords;
wherein the ML explanation engine uses a perturbation layer that provides perturbation as input to at least one of the first ML model and the second ML model based on an embedded layer, and
wherein the keyword list is determined based on model outputs from the perturbations generated by the perturbation layer.
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