International Business Machines Corporation

Qin Shirley Held

Munish Goyal

Steven M O'Brien, Jr

Jason Boada

Rachel Cohen

Dangaia Sims

Jeremy Chase

Gabriel Asaftei

A method and system for improving document lifecycle editing and storage technology is provided. The method includes enabling interactions between a user and a hardware controller. Editor profiles associated with editing privileges of the user are generated. The editor profiles include parameters generated based on a performance of past edits. The editing tasks are automated task difficulty attributes associated with a difficulty of executing the editing tasks are generated. The editing tasks may include readability and consolidation tasks. An optimized version of the editing tasks is assigned to software editors and time periods associated with the software editors completing the editing tasks are tracked. The optimized version of the editing tasks is generated based on the editor profiles and new tasks for assignment. User permissions and alerts are monitored and recommendation actions associated with the editing tasks are generated. The editing tasks are modified for future execution.

Automated editing task modification

A method and system for improving linguistic data and storage technology is provided. The method includes receiving data input text from a user and identifying text within the data input text. The data input text is edited and improvements in the data input text are detected via a machine learning process. In response, a modified version of the user interface is generated for allowing additional users to view and modify additional data input text. Change attributes associated with the data input text with respect to the modified version of the user interface are determined and alternative input suggestions are ranked. Editing data and code are generated in response to an editor engine interacting with a hardware controller. The editing data and code is executed thereby updating and modifying functions associated with software engines to increase an efficiency of future recommendations associated with future data input text analysis.

Updating and modifying linguistic based functions in a specialized user interface

For a task that has been partially executed, a residual complexity index is computed, the task being of a complexity that cannot be ascertained prior to executing the task. An evaluation is made whether the residual complexity index exceeds a cost of a resource that should be considered for allocation to the task. When the evaluation is affirmative, a priority of the task is established relative to a second task. The resource is scheduled to perform the task according to a timing, the timing being determined using the cost of the resource. The resource is allocated to the task according to the timing.

Resource allocation for tasks of unknown complexity

Aspects automatically minimize marketing rates as a function of optimized response rate models. Response rates are estimated from marketing offers targeted from a first entity to topic-entity pairs at respective specified marketing rates as a function of relative differences in their consumer sentiment scores. Marketing offers are targeted to a subset of the topic-entity pairs that each have estimated response rates meeting a threshold response rate constraint. Respective costs and actual rates of response from consumers are determined for the targeted offers. Response rates are modeled to determine modeled response parameters for the topics and entities of the subset topic-entity pairs as regressions of minimized differences in value between estimated and actual response rates. Marketing rates of the subset entity-topic pairs are minimized to meet the threshold response rate constraint and a marketing cost constraint as a function of the modeled response parameters.

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Midland Park, NJ, United States of America

Qin Shirley Held