A method for data-centric networked application development includes: modifying a graphical user interface of a networked application development environment with a selectable component for including a reusable data entity in a project, the reusable data entity being defined and bound to a form component via interaction with the graphical user interface; and configuring a block of a data-centric form of the project with the form component in response to selection of the selectable component at a design surface of the graphical user interface.

Systems and methods are provided for operating a user-controllable parameter. An item pool is accessed, where the item pool contains a plurality of items, and where each item is associated with a parameter. A baseline position is identified, where the baseline position is associated with a particular value of the parameter. A user-controllable parameter is received, where the user-controllable parameter indicates a user preference for a next item relative to the baseline position. The next item is selected based on the baseline position and the user-controllable parameter, and the next item is provided via a computer network.

Systems and methods are provided for operating a user-controllable parameter. An item pool is accessed, where the item pool contains a plurality of items, and where each item is associated with a parameter. A baseline position is identified, where the baseline position is associated with a particular value of the parameter. A user-controllable parameter is received, where the user-controllable parameter indicates a user preference for a next item relative to the baseline position. The next item is selected based on the baseline position and the user-controllable parameter, and the next item is provided via a computer network.

Methods, systems, and devices are provided for generating a graphical user interface configured to display, at least in part, a schedule. According to one aspect, the system can receive selectable fields of a client and selectable fields one or more providers from a plurality of providers. The system can determine the quality of pairings between the client and each of the one or more providers based on the one or more selectable fields of the client and the one or more selectable fields of the one or more providers. The system can generate a schedule of potential sessions based on the pairings. The system can score each of the potential sessions and display the schedule and scores to a user.

Methods, systems, and devices are provided for generating a graphical user interface configured to display, at least in part, a schedule. According to one aspect, the system can receive selectable fields of a client and selectable fields one or more providers from a plurality of providers. The system can determine the quality of pairings between the client and each of the one or more providers based on the one or more selectable fields of the client and the one or more selectable fields of the one or more providers. The system can generate a schedule of potential sessions based on the pairings. The system can score each of the potential sessions and display the schedule and scores to a user.

As described herein, a machine learning system, method, and computer program provide marketing segmentation of residential spaces. In use, network usage data is collected from each residential network router of a plurality of residential network routers operating in a different residential space of a plurality of residential spaces. Additionally, the network usage data is processed by a machine learning algorithm to segment the plurality of residential spaces into a plurality of segments. Further, the plurality of segments are output.

As described herein, a machine learning system, method, and computer program provide marketing segmentation of residential spaces. In use, network usage data is collected from each residential network router of a plurality of residential network routers operating in a different residential space of a plurality of residential spaces. Additionally, the network usage data is processed by a machine learning algorithm to segment the plurality of residential spaces into a plurality of segments. Further, the plurality of segments are output.

Systems and methods for automatically locating web-based social network members are provided. According to one embodiment, contact content including an associated GPS identifier and status for web-based social network members located at or near the same location automatically appears on a GPS-enabled device. A further exemplary system includes a GPS-enabled device configured to receive a GPS identifier and a status representing a location and a current state for a web-based social network member, a processing module that associates the received GPS-identifier and the received status, and a communications module that sends the associated GPS-identifier and status to a server comprising a web-based social network database. Contact content in a web-based social network database record in the web-based social network database is updated to include the associated GPS identifier and status for the web-based social network member.

A computer-implemented method for controlling content distribution includes forwarding information associated with a user to a device operated by the user, the information being configured for use in selecting content from any of multiple content providers for a content distribution to the user. The method includes receiving, in response to the information, an edit of the information forwarded from the device. The edit identifies a first content provider and including a first modification of the content distribution regarding the first content provider. The method includes storing the edit in association with the information such that the first modification is taken into account in the content distribution. The method can be implemented using a computer program product tangibly embodied in a computer-readable storage medium.

Methods, systems, devices, and software are disclosed for generating a network usage profile. Certain embodiments of the network usage profile include a devices-by-node profile, indicating the set of customer devices available for use in communicating with a customer-side network node located at a customer side of an access network over a period of time, where some of the customer devices are not in operative communication with the customer-side network node during a portion of that time. Other embodiments associate the network usage profile with customer information to generate device-by-customer profiles. Still other embodiments associate the network usage profile with network traffic information to generate traffic-by-device profiles. Even other embodiments associate the multiple sources and types of information to generate traffic-by-customer profiles and/or traffic-by-device-by-customer profiles. Any of the profiles may then be accessed by one or more parties for use in affecting various network services, including targeting content delivery.