Examples of the disclosure enable an information processing system to automatically implement a user interaction diagnostic engine. In some examples, the information processing system analyzes documents to identify parameters associated with profile features and performance metrics. Based on the parameters, correlation values between the profile features and one or more performance metrics are determined. Based on the correlation values, at least one profile feature is identified to improve a parameter associated with the performance metrics. A predictive model associated with the profile features and the performance metrics is generated. One or more actionable items configured to modify the at least one profile feature are determined such that, based on the predictive model, a parameter associated with the performance metrics are predicted to improve upon execution of the one or more actionable items.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An information processing system comprising: a memory area storing a plurality of documents and computer-executable instructions for implementing a user interaction diagnostic engine; and a processor configured to execute the computer-executable instructions to: analyze the plurality of documents to identify a plurality of parameters associated with a plurality of profile features and a plurality of performance metrics; based on the identified plurality of parameters, determine a plurality of correlation values between the plurality of profile features and one or more performance metrics of the plurality of performance metrics; based on the determined plurality of correlation values, identify at least one profile feature of the plurality of profile features configured to improve one or more parameters associated with the one or more performance metrics; generate a predictive model associated with the plurality of profile features and the one or more performance metrics; and determine one or more actionable items configured to modify a parameter associated with the at least one identified profile feature such that, based on the generated predictive model, the one or more parameters associated with the one or more performance metrics are predicted to improve upon execution of the one or more actionable items. 2. The information processing system of claim 1, wherein the processor is configured to execute the computer-executable instructions to identify a parameter of the plurality of parameters based on content of at least one document of the plurality of documents. 3. The information processing system of claim 1, wherein the processor is configured to execute the computer-executable instructions to identify a parameter of the plurality of parameters based on a property of at least one document of the plurality of documents. 4. The information processing system of claim 1, wherein the processor is configured to execute the computer-executable instructions to: identify a first set of parameters associated with a first target segment, the plurality of parameters including the first set of parameters; and determine a first actionable item associated with the first target segment, the one or more actionable items including the first actionable item. 5. The information processing system of claim 4, wherein the processor is configured to execute the computer-executable instructions to: identify a second set of parameters associated with a second target segment, the plurality of parameters including the second set of parameters; and compare the first target segment with the second target segment to determine a second actionable item associated with one of the first target segment and the second target segment, the one or more actionable items including the second actionable item. 6. The information processing system of claim 5, wherein the processor is configured to execute the computer-executable instructions to: identify a third set of parameters associated with a first profile, the plurality of parameters including the third set of parameters; identify a fourth set of parameters associated with a second profile, the plurality of parameters including the fourth set of parameters; and compare the first profile with the second profile to determine a third actionable item associated with one of the first profile and the second profile, the one or more actionable items including the third actionable item. 7. The information processing system of claim 1, wherein the processor is configured to execute the computer-executable instructions to: identify one set of parameters associated with one target segment, the plurality of parameters including the one set of parameters; identify one or more other sets of parameters associated with one or more other target segments, the plurality of parameters including the one or more other sets of parameters; and compare the one target segment with the one or more other target segments to determine an actionable item associated with one of the one target segment and the one or more other target segments, the one or more actionable items including the actionable item. 8. The information processing system of claim 1, wherein the processor is configured to execute the computer-executable instructions to: identify one set of parameters associated with a first profile, the plurality of parameters including the one set of parameters; identify one or more other sets of parameters associated with a second profile, the plurality of parameters including the one or more other sets of parameters; and compare the first profile with the second profile to determine an actionable item associated with one of the first profile and the second profile, the one or more actionable items including the actionable item. 9. The information processing system of claim 1, wherein the processor is configured to execute the computer-executable instructions to determine whether the at least one profile feature is statistically relevant. 10. A computer-implemented method for implementing a user interaction diagnostic engine, the method comprising: retrieving, using a document collection module, a plurality of documents from a plurality of sources; analyzing, using a parameter extraction module, the plurality of documents to identify a plurality of parameters, the plurality of parameters associated with a plurality of profile features and a plurality of performance metrics; based on the identified plurality of parameters, determining, using a model generation module, one or more correlations between the plurality of parameters; determining, using the model generation module, one or more correlation values between the plurality of profile features and one or more performance metrics of the plurality of performance metrics; based on the one or more determined correlation values, identifying one or more profile features of the plurality of profile features configured to improve a parameter associated with at least one performance metric of the plurality of performance metrics; generating, using the model generation module, a predictive model associated with the plurality of parameters; determining, using an actionable item generation module, one or more actionable items associated with one or more modifications to a parameter associated with the one or more profile features that, using the generated predictive model, is predicted to improve the parameter associated with the at least one performance metric upon execution of the one or more actionable items. 11. The computer-implemented method of claim 10, wherein analyzing the plurality of documents comprises identifying a parameter of the plurality of parameters based on content of at least one document of the plurality of documents. 12. The computer-implemented method of claim 10, wherein analyzing the plurality of documents comprises identifying a parameter of the plurality of parameters based on a property of at least one document of the plurality of documents. 13. The computer-implemented method of claim 10, wherein analyzing the plurality of documents comprises: identifying one set of parameters associated with one target segment, the plurality of parameters including the one set of parameters; and identifying one or more other sets of parameters associated with one or more other target segments, the plurality of parameters including the one or more other sets of parameters; and wherein determining one or more actionable items comprises comparing the one target segment with the one or more other target segments to determine an actionable item associated with one of the one target segment and the one or more other target segments, the one or more actionable items including the actionable item. 14. The computer-implemented method of claim 10, wherein analyzing the plurality of documents comprises: identifying one set of parameters associated with a first profile, the plurality of parameters including the one set of parameters; and identifying one or more other sets of parameters associated with a second profile, the plurality of parameters including the one or more other sets of parameters; and wherein determining one or more actionable items comprises comparing the first profile with the second profile to determine an actionable item associated with one of the first profile and the second profile, the one or more actionable items including the actionable item. 15. The computer-implemented method of claim 10, wherein identifying one or more profile features comprises determining whether the one or more profile features are statistically relevant. 16. A system comprising: a parameter extraction module configured to analyze a plurality of documents to identify a plurality of parameters associated with a plurality of profile features and a plurality of performance metrics; a model generation module configured to determine a plurality of correlation values between the plurality of profile features and one or more performance metrics of the plurality of performance metrics based on the identified plurality of parameters, identify at least one profile feature of the plurality of profile features configured to improve one or more parameters associated with the one or more performance metrics based on the determined plurality of correlation values, and generate a predictive model associated with the plurality of profile features and the one or more performance metrics; and an actionable item generation module configured to determine one or more actionable items configured to modify a parameter associated with the at least one identified profile feature such that, based on the generated predictive model, the one or more parameters associated with the one or more performance metrics are predicted to improve upon execution of the one or more actionable items. 17. The system of claim 16, wherein the parameter extraction module is configured to identify a parameter of the plurality of parameters based on content of at least one document of the plurality of documents. 18. The system of claim 16, wherein the parameter extraction module is configured to identify a parameter of the plurality of parameters based on a property of at least one document of the plurality of documents. 19. The system of claim 16, wherein the parameter extraction module is configured to identify a first set of parameters associated with a first target segment, and the actionable item generation module is configured to determine a first actionable item associated with the first target segment, wherein the plurality of parameters includes the first set of parameters, and the one or more actionable items includes the first actionable item. 20. The system of claim 16, wherein the parameter extraction module is configured to identify one set of parameters associated with one target segment, and identify one or more other sets of parameters associated with one or more other target segments, and the actionable item generation module is configured to compare the one target segment with the one or more other target segments to determine an actionable item associated with one of the one target segment and the one or more other target segments, wherein the plurality of parameters includes the one set of parameters and the one or more other sets of parameters, and the one or more actionable items includes the actionable item.