Identifying search terms for an electronic document search engine

An information handling system comprising a processor having access to memory media storing instructions executable by the processor to perform operations, comprising:

• generating, using a market prediction model, market trend data associated with computing products, including:
• for each computing product:
• identifying electronic documents associated with the computing product;
• calculating, based on the electronic documents, product sentiment, market data, and financial data results associated with the computing product;
• and
• generating, using a market prediction model, the market trend data associated with the computing product based on the product sentiment, market data, and financial data results associated with the computing product;
• comparing the market trend data with the product profiles of each of the computing products;
• identifying, based on the comparing, target computing components and target features of the market trend data absent from the product profiles of the computing products;
• for one or more targeted computing products:
• iteratively generating, based on the target computing components, a plurality of layouts of the targeted computing product;
• iteratively permutating each of the plurality of layouts of the targeted computing product based on a plurality of combinations of the target features of each of the target computing components of each of the plurality of layouts;
• identifying, from a data store, a respective product profile of the computing products, including a list of a plurality of computing components associated with the computing products, wherein the list of the plurality of computing components includes, for each computing component, a plurality of features of the computing component;
• for each computing product:
• comparing the product profile of the computing product with each of the plurality of permutated layouts of a targeted computing product of the one or more targeted computing products;
• identifying, based on the comparing, a particular permutated layout that has a greatest difference in predicted workload with the computing product;
• creating a build of the particular permutated layout, wherein the build maximizes a compute capability of the computing product;
• and
• storing, at the storage device, a table indicating the particular permutated layout with respect to the computing product.

A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising:

• generating, using a market prediction model, market trend data associated with computing products, including:
• for each computing product:
• identifying electronic documents associated with the computing product;
• calculating, based on the electronic documents, product sentiment, market data, and financial data results associated with the computing product;
• and
• generating, using a market prediction model, the market trend data associated with the computing product based on the product sentiment, market data, and financial data results associated with the computing product;
• comparing the market trend data with the product profiles of each of the computing products;
• identifying, based on the comparing, target computing components and target features of the market trend data absent from the product profiles of the computing products;
• for one or more targeted computing products:
• iteratively generating, based on the target computing components, a plurality of layouts of the targeted computing product;
• iteratively permutating each of the plurality of layouts of the targeted computing product based on a plurality of combinations of the target features of each of the target computing components of each of the plurality of layouts;
• identifying, from a data store, a respective product profile of the computing products, including a list of a plurality of computing components associated with the computing products, wherein the list of the plurality of computing components includes, for each computing component, a plurality of features of the computing component;
• for each computing product:
• comparing the product profile of the computing product with each of the plurality of permutated layouts of a targeted computing product of the one or more targeted computing products;
• identifying, based on the comparing, a particular permutated layout that has a greatest difference in predicted workload with the computing product;
• creating a build of the particular permutated layout, wherein the build maximizes a compute capability of the computing product;
• and
• storing, at the storage device, a table indicating the particular permutated layout with respect to the computing product.