Abstract: Disclosed herein are embodiments for automated intelligent price guidance of listings for a for sale object (FSO) being offered by a seller. Some embodiments may operate by: receiving information relating to the FSO, including specifications for selling the FSO, wherein the specifications include an original offer price and a time window for selling the FSO; determining a category of the FSO; generating an optimal offer price for the FSO based on one or more of: (a) past listings of previously sold FSOs that have a same or similar category of the FSO; (b) the specifications, including the time window; (c) a category decay curve applicable to the category; and (d) seller flexibility curve of the seller; and through the use of a machine learning neural networking analysis suggesting the optimal offer price to the seller as an offer price for a listing corresponding to the FSO, wherein this price is evaluated over time and suggestions are made accordingly.

Abstract: A computational instance may contain queues configured to hold work items. The work items may be representations of user submissions requesting actions from a plurality of agents. The computational instance may also contain computing devices configured to: (a) obtain a set of assignment rules that specify mappings between (i) respective selection criteria for the assignment rules, and (ii) one or more candidate agents from the plurality of agents that can be assigned to address the work items with content that match the respective selection criteria, (b) read, from the queues, a work item corresponding to a user submission, (c) iterate through the assignment rules according to an ordering until a particular assignment rule with associated selection criteria that matches content of the work item is found, and (d) assign the work item to a particular agent from the one or more candidate agents.

Abstract: Systems and methods for conducting a test on a third-party testing platform are provided. A networked system causes presentation of a setup user interface to a third-party user, whereby the setup user interface includes a field for indicating an attribute of a publication to be tested. The networked system receives, via the setup user interface, an indication of the attribute, a subject to be tested, and one or more test parameters. The networked system applies the attribute change to a first version of the publication to generate a second version of the publication. The first version is presented to a first subset of potential users and the second version is presented to a second subset of potential users. Interactions with both the first version and the second version are monitored and analyzed to determine results of the test. The results are then presented to the third-party user.

Abstract: A dynamic experimentation evaluation system provides a framework in which a continuous stream of metric data is monitored to establish a causal relationship between changes in a software program and the effect of user-observable behavior. In one aspect, an A/B test is performed continuously on a stream of metric data representing the usage of a control version of software product and the usage of a treatment version of the software product. A sequential probability ratio test (SPRT) is used as the test statistic to determine when to terminate the test and produce results within a specific confidence interval and controlled error rate.

Abstract: A computer-implemented method includes assigning an auditor weight to each user of a plurality of users. A plurality of audit data is received from the plurality of users, where each audit data is associated with a respective user and includes a set of user ratings for an audit. Final ratings are generated for the audit, with a respective final rating for each item in the audit. Generating the final rating of a first item in the audit includes identifying, in the audit data, user ratings for the first item. The user ratings for the first item include a respective user rating of the first item from each user. Generating the final rating of a first item further includes calculating the final rating of the first item based on a weighted combination of the plurality of user ratings for the first item, according to the respective auditor weight of each user.

Abstract: An analysis method includes: executing first accumulation processing for accumulating analysis reports including an analysis item regarding an analysis target and analysis results with respect to the analysis item; executing first extraction processing for extracting the analysis item and texts representing the analysis results from each of the analysis reports accumulated; executing first identification processing for identifying analysis techniques corresponding to the texts extracted; executing generation processing for generating analysis patterns; executing second identification processing for identifying first analysis patterns; executing third identification processing for identifying other analysis patterns; executing second accumulation processing for accumulating pattern information; executing second extraction processing for extracting the analysis item and the texts from a new analysis report; and executing output processing for identifying an analysis technique.

Abstract: A device may receive organization data defining first capabilities of an organization and industry trend data that is relevant to the organization. The industry trend data may define second capabilities that are relevant to the organization. The device may provide, as input to a capability model, the organization data and the industry trend data. The capability model may have been trained to produce, as output, data specifying recommended changes for the organization. The device may determine, based on the output of the capability model and the industry trend data, a recommendation. The device may perform an action based on the recommendation.

Abstract: Methods, systems and computer program products for providing an interactive resource plan visualization associated with a facility are provided. Aspects include receiving facility data comprising historical facility data, current facility data and demand data. Aspects also include determining projected resource demand based on the facility data and the demand data and using cognitive computing techniques. Aspects also include generating a visual representation of a facility. The visual representation of the facility includes available resources and resource demand associated with a specified time and the available resources are rendered according to a first visual style. Aspects also include determining resource availability modifications based on the available resources and the projected resource demand. Aspects also include generating a visual representation of the resource availability modifications associated with the specified time within the visual representation of the facility.

Abstract: A computer-implemented method in a visualization module is provided. The visualization module comprises a processor configured by programming instructions encoded in non-transient computer readable media. The method comprises: receiving, by the processor from a user interface, a request for a visualization of decision steps made in an order allocation process; retrieving, by the processor from a database system, a plurality of data items belonging to the same order that identify rules applied at each decision step in the order allocation process, parameters used during rule application, and decisions resulting from rule application; generating, by the processor using the retrieved data items, a visualization that identifies the decision made at each decision step; and causing the visualization to be displayed on the user interface.