Abstract: Methods and systems for trend aware self-correcting entity relationship extraction are disclosed. For example, a method can include receiving a selected entity, determining a plurality of entities related to the selected entity, determining a plurality of most probable entities, calculating relevance scores, and displaying a subset of the plurality of most probable entities. The selected entity can be received on a network-based transaction system. The plurality of entities related to the selected entity can be determined based on a relationship score. The relationship score can represent navigation transitions, aggregated over time, between the selected entity and each of the plurality of entities. The plurality of most probable entities can be determined based on probabilities. Relevance scores can be calculated for each of the plurality of most probable entities. Finally, the subset of the plurality of most probable entities to be displayed can be determined according to the relevance scores.

Abstract: Methods and systems for extracting targeted data for real-time reporting are discussed. In an example, a system can include a data store, a server, and a denormalized database. The data store can maintain data created by an application. The server can be communicatively coupled to the data store. The server can include a data extraction module and a data compression module. The data extraction module can extract a subset of the data stored in the data store according to an extraction scheme. The data compression module can compress the extracted subset of the data into a set of aggregated key value pairs. The denormalized database can store the aggregated key value pairs.

Abstract: Methods and systems for trend aware self-correcting entity relationship extraction are disclosed. For example, a method can include receiving a selected entity, determining a plurality of entities related to the selected entity, determining a plurality of most probable entities, calculating relevance scores, and displaying a subset of the plurality of most probable entities. The selected entity can be received on a network-based transaction system. The plurality of entities related to the selected entity can be determined based on a relationship score. The relationship score can represent navigation transitions, aggregated over time, between the selected entity and each of the plurality of entities. The plurality of most probable entities can be determined based on probabilities. Relevance scores can be calculated for each of the plurality of most probable entities. Finally, the subset of the plurality of most probable entities to be displayed can be determined according to the relevance scores.

Abstract: Systems and methods disclosed herein accept a position along a length of a value-selection display screen widget. The value-selection widget is depicted in a graphical user interface that is displayed on a screen of a mobile device. A selection of the position along a length of the value-selection widget is received. A value corresponding to the position is determined. The determining is performed by relating a first ratio to a second ratio. The determined value corresponding to the position is displayed on the screen.

Abstract: Methods and systems for trend aware self-correcting entity relationship extraction are disclosed. For example, a method can include receiving a selected entity, determining a plurality of entities related to the selected entity, determining a plurality of most probable entities, calculating relevance scores, and displaying a subset of the plurality of most probable entities. The selected entity can be received on a network-based transaction system. The plurality of entities related to the selected entity can be determined based on a relationship score. The relationship score can represent navigation transitions, aggregated over time, between the selected entity and each of the plurality of entities. The plurality of most probable entities can be determined based on probabilities. Relevance scores can be calculated for each of the plurality of most probable entities. Finally, the subset of the plurality of most probable entities to be displayed can be determined according to the relevance scores.

Abstract: Methods and systems for extracting targeted data for real-time reporting are discussed. In an example, a system can include a data store, a server, and a denormalized database. The data store can maintain data created by an application. The server can be communicatively coupled to the data store. The server can include a data extraction module and a data compression module. The data extraction module can extract a subset of the data stored in the data store according to an extraction scheme. The data compression module can compress the extracted subset of the data into a set of aggregated key value pairs. The denormalized database can store the aggregated key value pairs.

Abstract: Methods and systems for extracting targeted data for real-time reporting are discussed. In an example, a system can include a data store, a server, and a denormalized database. The data store can maintain data created by an application. The server can be communicatively coupled to the data store. The server can include a data extraction module and a data compression module. The data extraction module can extract a subset of the data stored in the data store according to an extraction scheme. The data compression module can compress the extracted subset of the data into a set of aggregated key value pairs. The denormalized database can store the aggregated key value pairs.

Abstract: Methods and systems for trend aware self-correcting entity relationship extraction are disclosed. For example, a method can include receiving a selected entity, determining a plurality of entities related to the selected entity, determining a plurality of most probable entities, calculating relevance scores, and displaying a subset of the plurality of most probable entities. The selected entity can be received on a network-based transaction system. The plurality of entities related to the selected entity can be determined based on a relationship score. The relationship score can represent navigation transitions, aggregated over time, between the selected entity and each of the plurality of entities. The plurality of most probable entities can be determined based on probabilities. Relevance scores can be calculated for each of the plurality of most probable entities. Finally, the subset of the plurality of most probable entities to be displayed can be determined according to the relevance scores.

Abstract: Methods and systems for trend aware self-correcting entity relationship extraction are disclosed. For example, a method can include receiving a selected entity, determining a plurality of entities related to the selected entity, determining a plurality of most probable entities, calculating relevance scores, and displaying a subset of the plurality of most probable entities. The selected entity can be received on a network-based transaction system. The plurality of entities related to the selected entity can be determined based on a relationship score. The relationship score can represent navigation transitions, aggregated over time, between the selected entity and each of the plurality of entities. The plurality of most probable entities can be determined based on probabilities. Relevance scores can be calculated for each of the plurality of most probable entities. Finally, the subset of the plurality of most probable entities to be displayed can be determined according to the relevance scores.

Abstract: Methods and systems for extracting targeted data for real-time reporting are discussed. In an example, a system can include a data store, a server, and a denormalized database. The data store can maintain data created by an application. The server can be communicatively coupled to the data store. The server can include a data extraction module and a data compression module. The data extraction module can extract a subset of the data stored in the data store according to an extraction scheme. The data compression module can compress the extracted subset of the data into a set of aggregated key value pairs. The denormalized database can store the aggregated key value pairs.

Abstract: Systems and methods disclosed herein accept a position along a length of a value-selection display screen widget. The value-selection widget is depicted in a graphical user interface that is displayed on a screen of a mobile device. A selection of the position along a length of the value-selection widget is received. A value corresponding to the position is determined. The determining is performed by relating a first ratio to a second ratio. The determined value corresponding to the position is displayed on the screen.

Abstract: Methods and systems for trend aware self-correcting entity relationship extraction are disclosed. For example, a method can include receiving a selected entity, determining a plurality of entities related to the selected entity, determining a plurality of most probable entities, calculating relevance scores, and displaying a subset of the plurality of most probable entities. The selected entity can be received on a network-based transaction system. The plurality of entities related to the selected entity can be determined based on a relationship score. The relationship score can represent navigation transitions, aggregated over time, between the selected entity and each of the plurality of entities. The plurality of most probable entities can be determined based on probabilities. Relevance scores can be calculated for each of the plurality of most probable entities. Finally, the subset of the plurality of most probable entities to be displayed can be determined according to the relevance scores.

Abstract: Methods and systems for extracting targeted data for real-time reporting are discussed. In an example, a system can include a data store, a server, and a denormalized database. The data store can maintain data created by an application. The server can be communicatively coupled to the data store. The server can include a data extraction module and a data compression module. The data extraction module can extract a subset of the data stored in the data store according to an extraction scheme. The data compression module can compress the extracted subset of the data into a set of aggregated key value pairs. The denormalized database can store the aggregated key value pairs.

Abstract: Systems and methods disclosed herein accept a user-selected adjustment position associated with a value-selection display screen widget. A non-linear calculation is performed on the user-selected adjustment position, a length of the screen widget, a smallest represented value associated with a range of values, a largest represented value associated with a range of values, and/or an adjustment granularity associated with the display screen widget. The non-linear calculation determines a selected value corresponding to the user-selected adjustment position. The selected value is then sent to a physical output device. Additional embodiments are disclosed and claimed.

Abstract: Methods and systems for trend aware self-correcting entity relationship extraction are disclosed. For example, a method can include receiving a selected entity, determining a plurality of entities related to the selected entity, determining a plurality of most probable entities, calculating relevance scores, and displaying a subset of the plurality of most probable entities. The selected entity can be received on a network-based transaction system. The plurality of entities related to the selected entity can be determined based on a relationship score. The relationship score can represent navigation transitions, aggregated over time, between the selected entity and each of the plurality of entities. The plurality of most probable entities can be determined based on probabilities. Relevance scores can be calculated for each of the plurality of most probable entities. Finally, the subset of the plurality of most probable entities to be displayed can be determined according to the relevance scores.

Abstract: Methods and systems for trend aware self-correcting entity relationship extraction are disclosed. For example, a method can include receiving a selected entity, determining a plurality of entities related to the selected entity, determining a plurality of most probable entities, calculating relevance scores, and displaying a subset of the plurality of most probable entities. The selected entity can be received on a network-based transaction system. The plurality of entities related to the selected entity can be determined based on a relationship score. The relationship score can represent navigation transitions, aggregated over time, between the selected entity and each of the plurality of entities. The plurality of most probable entities can be determined based on probabilities. Relevance scores can be calculated for each of the plurality of most probable entities. Finally, the subset of the plurality of most probable entities to be displayed can be determined according to the relevance scores.

Abstract: Methods and systems for trend aware self-correcting entity relationship extraction are disclosed. For example, a method can include receiving a selected entity, determining a plurality of entities related to the selected entity, determining a plurality of most probable entities, calculating relevance scores, and displaying a subset of the plurality of most probable entities. The selected entity can be received on a network-based transaction system. The plurality of entities related to the selected entity can be determined based on a relationship score. The relationship score can represent navigation transitions, aggregated over time, between the selected entity and each of the plurality of entities. The plurality of most probable entities can be determined based on probabilities. Relevance scores can be calculated for each of the plurality of most probable entities. Finally, the subset of the plurality of most probable entities to be displayed can be determined according to the relevance scores.

Abstract: In various exemplary embodiments, a system and method to provide customized combination packages is disclosed. The method includes receiving a selection of a plurality of items from a potential buyer, the selection of the plurality of items creating a customized combination package. Available transaction history for past transactions of similar items to the items of the customized combination package is provided to the potential buyer. An offer from the potential buyer is then received and provided to a seller selling the plurality of items for consideration.

Abstract: In various exemplary embodiments, a system and method to provide customized combination packages is disclosed. The method includes receiving a selection of a plurality of items from a potential buyer, the selection of the plurality of items creating a customized combination package. Available transaction history for past transactions of similar items to the items of the customized combination package is provided to the potential buyer. An offer from the potential buyer is then received and provided to a seller selling the plurality of items for consideration.

Abstract: Methods and systems for trend aware self-correcting entity relationship extraction are disclosed. For example, a method can include receiving a selected entity, determining a plurality of entities related to the selected entity, determining a plurality of most probable entities, calculating relevance scores, and displaying a subset of the plurality of most probable entities. The selected entity can be received on a network-based transaction system. The plurality of entities related to the selected entity can be determined based on a relationship score. The relationship score can represent navigation transitions, aggregated over time, between the selected entity and each of the plurality of entities. The plurality of most probable entities can be determined based on probabilities. Relevance scores can be calculated for each of the plurality of most probable entities. Finally, the subset of the plurality of most probable entities to be displayed can be determined according to the relevance scores.