Content editing using AI-based content modeling

Abstract

A method of content production (e.g., content editing) using content modeling to facilitate content production. In one embodiment, an automated process is configured to render content. For a given content portion, and as the given portion is being rendered, the portion is processed to generate a content model. With respect to a concept expressed in or otherwise associated with the content, the system compares the content model with a target content derived model to generate a relevancy score. The target content derived model is generated by (a) identifying a set of target content portions in which the concept is expressed, (b) generating from each content portion an associated target content model; and (c) performing a vector operation on the associated target content models. Preferably, each associated target content model is built using an Artificial Intelligence (AI)-based content analysis. The relevancy score is used to generate a content production recommendation.

What is claimed is as follows: 
     
         1 . A method of content production, comprising:
 for a phrase within a given portion of content being rendered, generating a content model;   with respect to the phrase, comparing the content model with a target content derived model to generate a semantic relevancy score, the target content derived model having been generated by sub-steps comprising (a) identifying a set of search engine-indexed third party target content portions in which the key phrase is expressed, (b) generating from each search engine-indexed third party content portion an associated target content model, wherein each associated target content model is implemented as a semantic representation vector that encodes language and usage information representing a semantic depth and breadth of the key phrase as expressed in the associated third party target content portion, and further wherein at least one associated target content model is built by examining the associated third party target content portion for presence of one or more semantic meanings; and (c) performing a vector operation on the semantic representation vectors of the associated target content models; and   using the target content derived model to generate a content production recommendation;   wherein the semantic relevancy score indicates a degree to which the phrase is expressed in or otherwise associated with the content so as to bias a search engine to include a document that includes the content.