A computer-implemented method, computer program product and computing system for receiving a complex task; processing the complex task to define a plurality of discrete tasks each having a discrete goal; executing the plurality of discrete tasks on a plurality of machine-accessible public computing platforms; determining if any of the plurality of discrete tasks failed to achieve its discrete goal; and if a specific discrete task failed to achieve its discrete goal, defining a substitute discrete task having a substitute discrete goal.

A computer-implemented method, computer program product and computing system for receiving a complex task; processing the complex task to define a plurality of discrete tasks each having a discrete goal; executing the plurality of discrete tasks on a plurality of machine-accessible public computing platforms; determining if any of the plurality of discrete tasks failed to achieve its discrete goal; and if a specific discrete task failed to achieve its discrete goal, defining a substitute discrete task having a substitute discrete goal.

Methods and apparatus for extracting structured data from weblogs are disclosed. In some examples, the methods and apparatus include a web crawler to access a home page of a weblog, and identify a feed associated with the weblog. The methods and apparatus also include a feed finder to determine whether items in the feed contain sufficient content for feed-guided segmentation. The methods and apparatus also include a feed classifier to determine whether the items in the feed contain full content of the weblog. The methods and apparatus also include a wrapper to map data found in the feed into a representation of a weblog post, and screen scrape the weblog into the representation of the weblog post.

Methods and apparatus for extracting structured data from weblogs are disclosed. In some examples, the methods and apparatus include a web crawler to access a home page of a weblog, and identify a feed associated with the weblog. The methods and apparatus also include a feed finder to determine whether items in the feed contain sufficient content for feed-guided segmentation. The methods and apparatus also include a feed classifier to determine whether the items in the feed contain full content of the weblog. The methods and apparatus also include a wrapper to map data found in the feed into a representation of a weblog post, and screen scrape the weblog into the representation of the weblog post.

Technologies are described herein for executing queries expressed with reference to a structured query language against unstructured data. A user issues a structured query through a traditional structured data management (“SDM”) application. Upon receiving the structured query, an SDM driver analyzes the structured query and extracts a data structure from the unstructured data, if necessary. The structured query is then converted to an unstructured query based on the extracted data structure. The converted unstructured query may then be executed against the unstructured data. Results from the query are reorganized into structured data utilizing the extracted data structure and are then presented to the user through the SDM application.

Technologies are described herein for executing queries expressed with reference to a structured query language against unstructured data. A user issues a structured query through a traditional structured data management (“SDM”) application. Upon receiving the structured query, an SDM driver analyzes the structured query and extracts a data structure from the unstructured data, if necessary. The structured query is then converted to an unstructured query based on the extracted data structure. The converted unstructured query may then be executed against the unstructured data. Results from the query are reorganized into structured data utilizing the extracted data structure and are then presented to the user through the SDM application.

Embodiments use successive refinement to allow a user to systematically explore the result set of an arbitrary query over RDF, such as a SPARQL query. A user inputs an arbitrary base query and modifies this query by replacing selected variables with values to which each selected variable is bound within the result set of the base query. Embodiments present, via a GUI, variable facets that may be substituted for query variables. Embodiments also present, through a GUI, a query history graph that represents query versions that a user has created. A user may navigate this query history graph to return to previously-created query versions. The GUI also provides information about the facets, including a number of results that would be included in the result set of the query version resulting from substitution of the facet for the associated variable.

Embodiments use successive refinement to allow a user to systematically explore the result set of an arbitrary query over RDF, such as a SPARQL query. A user inputs an arbitrary base query and modifies this query by replacing selected variables with values to which each selected variable is bound within the result set of the base query. Embodiments present, via a GUI, variable facets that may be substituted for query variables. Embodiments also present, through a GUI, a query history graph that represents query versions that a user has created. A user may navigate this query history graph to return to previously-created query versions. The GUI also provides information about the facets, including a number of results that would be included in the result set of the query version resulting from substitution of the facet for the associated variable.

Systems for locating server nodes for edge devices using latency-based georouting. At least one cloud platform including at least one cloud platform router and a node database is in network communication with at least one edge device and a plurality of server nodes. The at least one cloud platform receives an initial hypertext transfer protocol (HTTP) request from the at least one edge device. The node database is queried using the at least one cloud platform router and node data is fetched from the plurality of server nodes using an object-oriented function. A query result is returned indicating a nearest node from the plurality of server nodes. The HTTP request is responded to with a unique hypertext markup language (HTML) web page, and the HTTP request is executed using the nearest node.

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.