One example of a system comprises using a processor for identifying a model to be validated that is stored in a repository; automatically computing and recording one or more model metrics for the model to be validated in a tamper-proof manner; comparing the computed tamper-proof metrics with one or more encoded rules and policies to determine if the model to be validated complies with the one or more encoded rules and policies; and outputting a notification to a device indicating a validation status of the model to be validated based on the comparison of the computed tamper-proof metrics with the one or more encoded rules and policies.

Aspects of the disclosure relate to application mapping and alerting based on data dependencies in business and technology logic. In some embodiments, a computing platform may receive a request to map enterprise technology resources. Then, the computing platform may generate a business capability model. Next, the computing platform may cause a user computing device to display a graphical user interface comprising selectable graphical representations of applications associated with the enterprise technology resources. Then, the computing platform may receive a user input identifying an occurrence of a technology incident by selecting one of the graphical representations. In response to the selection, the computing platform may trace, using the generated business capability model, upstream or downstream impacts of the technology incident. Then, the computing platform may cause a visual representation of data dependencies indicating upstream or downstream impacts of the technology incident to be displayed on the user computing device.

Aspects of the disclosure relate to application mapping and alerting based on data dependencies in business and technology logic. In some embodiments, a computing platform may receive a request to map enterprise technology resources. Then, the computing platform may generate a business capability model. Next, the computing platform may cause a user computing device to display a graphical user interface comprising selectable graphical representations of applications associated with the enterprise technology resources. Then, the computing platform may receive a user input identifying an occurrence of a technology incident by selecting one of the graphical representations. In response to the selection, the computing platform may trace, using the generated business capability model, upstream or downstream impacts of the technology incident. Then, the computing platform may cause a visual representation of data dependencies indicating upstream or downstream impacts of the technology incident to be displayed on the user computing device.

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of: providing a search engine that includes, or communicates with, a recall personalization model configured to generate personalized recall sets of search results for users; receiving, at the search engine, a search query submitted by a user; generating, using the recall personalization module, a feature vector for the user that includes contextual features associated with the user; generating, using the recall personalization model, a simulated narrowing query that includes the search query submitted by the user and the feature vector; generating, using the search engine, a recall set of search results based, at least in part, on the simulated narrowing query. Other embodiments are disclosed herein.

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of: providing a search engine that includes, or communicates with, a recall personalization model configured to generate personalized recall sets of search results for users; receiving, at the search engine, a search query submitted by a user; generating, using the recall personalization module, a feature vector for the user that includes contextual features associated with the user; generating, using the recall personalization model, a simulated narrowing query that includes the search query submitted by the user and the feature vector; generating, using the search engine, a recall set of search results based, at least in part, on the simulated narrowing query. Other embodiments are disclosed herein.

Systems and methods for modeling and analysis of commerce platform system infrastructure provided by cloud services provider systems to a commerce platform are described. The method may include receiving a cloud services provider spending report generated by a cloud service provider system, wherein the cloud services provider spending report comprises information indicative of costs of cloud services provider resource usage by the commerce platform system over a period of time, and receiving a service report for one or more systems of the commerce platform, wherein the service report comprises information indicative of execution of services of the one or more systems of the commerce platform over the period of time. A directed graph may then be generated that models costs of commerce platform system service usage at the cloud services provider system. The method may also include performing an analysis of the directed graph to attribute cloud service provider system cost information to the commerce platform system service usage at the cloud services provider system, and generating a report indicating cloud service provider system costs attributable services of the commerce platform system.

Systems and methods for modeling and analysis of commerce platform system infrastructure provided by cloud services provider systems to a commerce platform are described. The method may include receiving a cloud services provider spending report generated by a cloud service provider system, wherein the cloud services provider spending report comprises information indicative of costs of cloud services provider resource usage by the commerce platform system over a period of time, and receiving a service report for one or more systems of the commerce platform, wherein the service report comprises information indicative of execution of services of the one or more systems of the commerce platform over the period of time. A directed graph may then be generated that models costs of commerce platform system service usage at the cloud services provider system. The method may also include performing an analysis of the directed graph to attribute cloud service provider system cost information to the commerce platform system service usage at the cloud services provider system, and generating a report indicating cloud service provider system costs attributable services of the commerce platform system.

New and improved methods and systems for modeling the performance of selected company metrics. Multiple, non-traditional sets of objective data along with mathematical analytical techniques are used to provide transparency and visibility into company performance relating to the particular metrics. Company inflection points and changes in strategy may be identified. The performance of a company and/or the performance of a selected industry or industry sector may be analyzed.

New and improved methods and systems for modeling the performance of selected company metrics. Multiple, non-traditional sets of objective data along with mathematical analytical techniques are used to provide transparency and visibility into company performance relating to the particular metrics. Company inflection points and changes in strategy may be identified. The performance of a company and/or the performance of a selected industry or industry sector may be analyzed.

Provided is a method and apparatus for predicting oil and gas yields in in-situ oil shale exploitation, the method includes: acquiring an original TOC value, a Ro value and an original HI value of a shale to be measured; and obtaining oil and gas yields in in-situ exploitation of the shale based on the original TOC value, Ro value, original HI value thereof and pre-established models for predicting oil and gas yields in in-situ oil shale exploitation, the models are pre-established based on oil and gas yield data obtained by performing a thermal simulation experiment on a plurality of different shale samples, and the original TOC value, Ro value and original HI value thereof. The above technical solution achieves a quantitative prediction of oil and gas yields in in-situ oil shale exploitation, and improves the accuracy and efficiency of prediction of oil and gas yields in in-situ oil shale exploitation.