An apparatus in one embodiment comprises a processing platform comprising one or more processing devices. The processing platform implements a database configured to store metric and level information for each of a plurality of models, and a metric mapper adapted to interface with the database. The metric mapper is configured to utilize the metric and level information stored in the database to establish an association between a first metric characterizing at least one of a workload and a resource in accordance with a first one of the models and a second metric characterizing at least one of a workload and a resource in accordance with a second one of the models. The established association is illustratively applied to relate service requirements specified at least in part using the first metric of the first model to service capabilities specified at least in part using the second metric of the second model.

A method involves managing electronic documents (EDs). The method includes receiving a first request to convert an original ED including a visible object from a first format to a second format; extracting, in response to the first request, multiple attributes in the original ED specifying the visible object and required to restore the visible object in the first format; generating, by converting the original ED from the first format to the second format, a converted ED including rendering data of the visible object that is grammatically native to the second format and that is necessary to render the visible object from the second format; and embedding the attributes extracted from the original ED into metadata of the converted ED.

A decision method for specifying an association relationship between attributes included in different documents is disclosed. The method includes: accepting a first attribute relating to items included in a first document and a second attribute relating to items included in a second document; specifying a first item associated with the accepted first attribute and a second item associated with the accepted second attribute; specifying a third item having a specific relationship to the specified first item and a fourth item having a specific relationship to the specified second item; and deciding, based on consistency between the specified third item and the specified fourth item, whether or not the first attribute is associated with the second attribute.

Systems, computer-implemented methods, and non-transitory computer-readable media are provided for on-boarding client data received from multiple information sources. Consistent with the disclosed embodiments, a computer system may receive metadata concerning information received from one or more information sources. The computer system may receive instructions for mapping the information onto a schema of a trait-based modeling system. Based on these received instructions, the computer system may generate a script for on-boarding the client data. The computer system may provide the script to a server, which may execute the script, causing the resulting information to be provided to a trait-based modeling system to optimize a field in the schema of the trait-based modeling system.

Embodiments relate to converting semi-structured spatial data. Initially, semi-structured spatial data is recursively traversed to determine a dynamically nested structure. The dynamically nested structure is translated into an application specific layer structure based on feature type grouping and display capabilities of a geographic information system (GIS) application. Next, an input symbology is determined for each feature in the semi-structured spatial data. The input symbology of each feature is analyzed to determine an application symbology for each map layer in the GIS application. A spatial database is created for the GIS application based on the application specific layer structure. The features are translated from the semi-structured spatial data into the spatial database, and the application symbology of each map layer is used to render the features in the GIS application.

This disclosure relates to systems and methods for using a uniform resource locator to retrieve content for both a first application and a second application. The user may elect to use the first or second application to view content associated with the uniform resource locator. In one instance, an unmodified uniform resource locator may be parsed for identifiers that may be used to retrieve content for the second application instead of the content for the first application. In another instance, a modified uniform resource locator may be appended with a second application scheme and a path for the content of the second application address. In both instances, the unmodified and the modified uniform resource locators may be used to retrieve content for the first application or the second application.

A computer-implemented method producing an inductive virtual sensor model of a target device within an ecosystem of devices includes a computing system identifying a first subset of devices in the ecosystem of devices. Each device in the first subset comprises a target sensor and additional sensors. The computing system collects target sensor data from the target sensor of each device in the first subset of devices, and additional sensor data from the additional sensors of each device in the first subset. A predictive model is trained to predict the target sensor data based on the additional sensor data. The computing system identifies a second subset of devices in the ecosystem of devices lacking the target sensor. Each device in the second subset of devices comprises the plurality of additional sensors. The computing system distributes the predictive model to each device in the second subset of devices.

With the scale of information available today along with the existing diverse channels of communication, manual processing of information is becoming a challenge and companies across industries are under tremendous pressure to lower transactional costs. Artificial Intelligence based automation of business transactions has seen regulatory hurdles due to probabilistic nature of the outcome. The main challenge lies in processing of transactions with unstructured information. Systems and methods of the present disclosure uses deterministic as well as probabilistic approaches to maximize accuracy. The larger use of deterministic approach with configurable components and ontologies helps to improvise accuracy, precision and reduce recall. The probabilistic approach is used when there is absence of quality information or less information for learning. Also, confidence indicators are provided at attribute level of data being processed and at each decision level.

A transformation engine that enables content and information to be transformed from one format, a source format, to a format that is compatible with the requesting device, a destination format. Advantageously, various device types can access and share content via a network without concern as to the original format of the content. When a client device provides a request for content, the transformation engine identifies delivery characteristics of the client device, and identifies a source for the requested content. The transformation engine then transforms the source formatted content into a format identified through a best fit analysis of the delivery characteristics of the device.

Embodiments of a distribution management system are disclosed. In some embodiments, a distribution management system enables to effectively provide geographic information system (GIS) data regarding an electric power application model applied to a supervisory control and data acquisition (SCADA) system using an international electrotechnical commission (IEC)-61968 standard, is a distribution management system based on IEC-61968, includes a GIS tool for generating GIS schema data, a GIS transfer unit for receiving the GIS schema data to transform the received GIS schema data into a format suitable for a standard, and one or more GIS distribution management applications connected to the GIS tool to receive the GIS schema data.