In one implementation, a data transformation engine is employed to analyze an incoming JSON schema syntax and use a “best effort” model to convert a plurality of JSON schemas to other types of schemas such as an XML schema. The model is configured to be adaptable and dynamic in order to convert as much of the JSON as possible. In addition, the conversion tool is configured to transform schemas to other technologies and allow for conversion errors within one or more error thresholds. Further, the system may be distributed standalone with no dependencies to other implementations, such as BPM implementations.

In one embodiment, the present invention includes a computer-implemented method comprising storing data in an application using an application custom data type and application custom data structure. The data is stored in a database using the application custom data type and the application custom data structure. In one embodiment, a request is sent to access the data from the application to the database. The data is retrieved from the database in response to the request in the application custom data type and the application custom data structure. In one embodiment, the data is sent from the database to a shared memory in the application custom data type and the application custom data structure and the data is retrieved by the application from the shared memory in the application custom data type and the application custom data structure.

Integrating a plurality of third party service interactions into a portal including a Web content management system includes receiving a data structure, associating the data structure with a selected profile out of a plurality of profiles based on the origin of the data structure, and transforming content of the received data structure, using a declarative mapping associated with the selected profile, into an intermediate data structure. The intermediate data structure may be provided to a presentation layer of the portal. A signal causing a rendering of the intermediate data structure may be triggered via a portlet of the portal to a display. Captured input from the portlet from the intermediate data structure may be transformed to the data structure using the declarative mapping associated with the selected profile. The data structure may be sent.

Integrating a plurality of third party service interactions into a portal including a Web content management system includes receiving a data structure, associating the data structure with a selected profile out of a plurality of profiles based on the origin of the data structure, and transforming content of the received data structure, using a declarative mapping associated with the selected profile, into an intermediate data structure. The intermediate data structure may be provided to a presentation layer of the portal. A signal causing a rendering of the intermediate data structure may be triggered via a portlet of the portal to a display. Captured input from the portlet from the intermediate data structure may be transformed to the data structure using the declarative mapping associated with the selected profile. The data structure may be sent.

A method and system for generating and using a master entity associative data network. The master entity associative data network system includes data sources storing data entities. Each data entity is of a specific entity type having specific entity properties, associations to other data entities, and an assigned common identifier label. Also, the master entity associative data network system includes a data processor configured to extract data entities from the data sources and extract associations to other data entities. The data processor stitches the data entities to each other based on at least one or more of the extracted associations, specific entity properties, and the common identifier label to generate one or more master data entities.

A method and system for generating and using a master entity associative data network. The master entity associative data network system includes data sources storing data entities. Each data entity is of a specific entity type having specific entity properties, associations to other data entities, and an assigned common identifier label. Also, the master entity associative data network system includes a data processor configured to extract data entities from the data sources and extract associations to other data entities. The data processor stitches the data entities to each other based on at least one or more of the extracted associations, specific entity properties, and the common identifier label to generate one or more master data entities.

A method includes obtaining feature generation code from, which is configured to determine features relating to input data. The method further includes obtaining data grouping code, which is configured to generate training data by determining a plurality of data groupings for the features relating to the input data. The method further includes obtaining modeling code, which is derived at least in part by applying one or more machine learning algorithms to the training data. The method further includes applying a model wrapper code to the feature generation code, the data grouping code, and the modeling code to generate a model wrapper and deploying the model wrapper such that the model wrapper may receive a first application programming interface (API) call including an input data value, determine a score relating to the input data value, and send a second API call including the score in response to the first API call.

A method includes obtaining feature generation code from, which is configured to determine features relating to input data. The method further includes obtaining data grouping code, which is configured to generate training data by determining a plurality of data groupings for the features relating to the input data. The method further includes obtaining modeling code, which is derived at least in part by applying one or more machine learning algorithms to the training data. The method further includes applying a model wrapper code to the feature generation code, the data grouping code, and the modeling code to generate a model wrapper and deploying the model wrapper such that the model wrapper may receive a first application programming interface (API) call including an input data value, determine a score relating to the input data value, and send a second API call including the score in response to the first API call.

A method of setting a surveillance camera includes the steps of recognizing a readable object in an image captured by the surveillance camera, updating a set value of one or more set items of the surveillance camera associated with the readable object, and transmitting the set value of an at least one set item to an external device in response to receiving a request therefrom.

A method of setting a surveillance camera includes the steps of recognizing a readable object in an image captured by the surveillance camera, updating a set value of one or more set items of the surveillance camera associated with the readable object, and transmitting the set value of an at least one set item to an external device in response to receiving a request therefrom.