Abstract: Methods and systems are provided to determine a partner fee recommendation. Such a partner fee may be a flat fee, percentage-based fee, or both, that a marketplace provider charges for sellers to use their platform. The partner fee recommendation may be calculated based on a plurality of factors. The partner fee recommendation may be based on data from a plurality of marketplaces. At least a portion of such data may be collected by a payment service provider or other service provider that provides services at multiple levels of transactions and through a plurality of marketplace platforms.

Abstract: Methods and systems are provided to determine a partner fee recommendation. Such a partner fee may be a flat fee, percentage-based fee, or both, that a marketplace provider charges for sellers to use their platform. The partner fee recommendation may be calculated based on a plurality of factors. The partner fee recommendation may be based on data from a plurality of marketplaces. At least a portion of such data may be collected by a payment service provider or other service provider that provides services at multiple levels of transactions and through a plurality of marketplace platforms.

Abstract: Methods and systems are provided to determine a partner fee recommendation. Such a partner fee may be a flat fee, percentage-based fee, or both, that a marketplace provider charges for sellers to use their platform. The partner fee recommendation may be calculated based on a plurality of factors. The partner fee recommendation may be based on data from a plurality of marketplaces. At least a portion of such data may be collected by a payment service provider or other service provider that provides services at multiple levels of transactions and through a plurality of marketplace platforms.

Abstract: A compact binary encoding technique for information that is logically hierarchically structured, such as XML data, maintains all of the features of XML data in a useable form, such as the hierarchical structure underlying the data. Hence, data encoded in this format can undergo XML-based processing on-the-fly as it is being received or fetched, as if the data was being processed linearly in its textual character-based format. Processing of data encoded in this format can begin without having to wait for and decode the entire data set. The overhead due to XML tags is significantly minimized. The encoded data can be processed more efficiently because the data is pre-parsed. Values may be stored in their native type formats and, therefore, processing of the encoded data avoids costly type conversions. Further, any available structural constraint information can be effectively exploited.

Abstract: Described herein are approaches that allow an XML entity to be accessed in a way that requires less memory. These approaches involve dynamically generating and maintaining an in-memory representation of only a portion of an XML tree. The in-memory representation of an XML tree is herein referred to as a node tree. The node tree contains data from the XML tree, and is generated by extracting data from a compressed form of an XML entity. In addition, the node tree contains information about the location of specific elements within the compressed XML entity. The approaches described herein allow an XML tree to be accessed without having to generate an in-memory representation of the whole XML tree, thus reducing the amount of memory needed to access the data in the XML tree.

Abstract: A compact binary encoding technique for information that is logically hierarchically structured, such as XML data, maintains all of the features of XML data in a useable form, such as the hierarchical structure underlying the data. Hence, data encoded in this format can undergo XML-based processing on-the-fly as it is being received or fetched, as if the data was being processed linearly in its textual character-based format. Processing of data encoded in this format can begin without having to wait for and decode the entire data set. The overhead due to XML tags is significantly minimized. The encoded data can be processed more efficiently because the data is pre-parsed. Values may be stored in their native type formats and, therefore, processing of the encoded data avoids costly type conversions. Further, any available structural constraint information can be effectively exploited.