Abstract: A system for payment routing programmed to: receive a payment transaction message relating to a putative transaction, the payment transaction message containing putative transaction data identifying an accountholder and a transaction amount corresponding to the putative transaction; input historical transaction data for the accountholder and at least a portion of the transaction amount to a scaled score algorithm to generate scaled scores, each of the scaled scores representing the likelihood of settlement of the putative transaction on a corresponding date and payment rail; output the scaled scores to a merchant in response to the payment transaction message; receive, from the merchant and in response to the output, feedback data for the putative transaction, the feedback data including a date of attempted payment processing for the putative transaction and an indicator of whether the attempted payment processing was completed; and retrain the scaled score algorithm using the feedback data.

Abstract: A system for payment routing programmed to: receive a payment transaction message relating to a putative transaction, the payment transaction message containing putative transaction data identifying an account of an accountholder and a transaction amount corresponding to the putative transaction; input at least some of the putative transaction data to a scaled score algorithm to generate a scaled score representing the likelihood of settlement of the putative payment transaction on a date, the scaled score algorithm including a plurality of components each respectively outputting a value and the scaled score being based on the plurality of values; generate metadata regarding the scaled score by applying a plurality of contribution rules to the values, the metadata comprising significance indicators for the components with respect to the generation of the scaled score; and output the scaled score and the metadata regarding the scaled score in response to the payment transaction message.

Abstract: A system for payment routing programmed to: receive a payment transaction message relating to a putative transaction, the payment transaction message containing putative transaction data identifying an accountholder and a transaction amount corresponding to the putative transaction; input historical transaction data for the accountholder and at least a portion of the transaction amount to a scaled score algorithm to generate scaled scores for corresponding potential settlement dates, each of the scaled scores representing the likelihood of settlement of the putative transaction from an account of the accountholder on the corresponding one of the potential settlement dates; retrieve, from a financial institution corresponding to the account, actual account balances for the account on the corresponding potential settlement dates; and retrain the scaled score algorithm using the actual account balances.

Abstract: A network device determines when multiple users each connect to a network using one or more devices. The network device obtains device or network-related parameters associated with the one or more devices and generates profiling vectors for each of the multiple users, that connects to the network using the one or more devices, to produce multiple profiling vectors. The network device clusters the multiple profiling vectors to identify cluster centers associated with a plurality of user groups, and determines first users of the multiple users for, or with, whom to perform certain actions or activities based on the first users' with one or more of the plurality of user groups. The network device performs the certain actions or activities with respect to the determined first users.

Abstract: A system for payment routing according to a likelihood of settlement. The system includes processors and/or transceivers programmed to receive a payment transaction message relating to a putative payment transaction. The payment transaction message contains putative payment transaction data including a customer identification (ID) for an account and a transaction amount. The system generates a scaled score representing the likelihood of settlement of the putative payment transaction on at least one date for each of a plurality of potential payment rails. Based at least in part on the at least one scaled score for each of the plurality of potential payment rails, the system selects a payment rail from the plurality of payment rails. The system initiates, via the selected payment rail, a payment transaction corresponding to the putative payment transaction.

Abstract: A network device determines when multiple users each connect to a network using one or more devices. The network device obtains device or network-related parameters associated with the one or more devices and generates profiling vectors for each of the multiple users, that connects to the network using the one or more devices, to produce multiple profiling vectors. The network device clusters the multiple profiling vectors to identify cluster centers associated with a plurality of user groups, and determines first users of the multiple users for, or with, whom to perform certain actions or activities based on the first users' affinity with one or more of the plurality of user groups. The network device performs the certain actions or activities with respect to the determined first users.

Abstract: A network device determines when multiple users each connect to a network using one or more devices. The network device obtains device or network-related parameters associated with the one or more devices and generates profiling vectors for each of the multiple users, that connects to the network using the one or more devices, to produce multiple profiling vectors. The network device clusters the multiple profiling vectors to identify cluster centers associated with a plurality of user groups, and determines first users of the multiple users for, or with, whom to perform certain actions or activities based on the first users' affinity with one or more of the plurality of user groups. The network device performs the certain actions or activities with respect to the determined first users.

Abstract: A network device determines when multiple users each connect to a network using one or more devices. The network device obtains device or network-related parameters associated with the one or more devices and generates profiling vectors for each of the multiple users, that connects to the network using the one or more devices, to produce multiple profiling vectors. The network device clusters the multiple profiling vectors to identify cluster centers associated with a plurality of user groups, and determines first users of the multiple users for, or with, whom to perform certain actions or activities based on the first users' affinity with one or more of the plurality of user groups. The network device performs the certain actions or activities with respect to the determined first users.

Abstract: A network device determines when multiple users each connect to a network using one or more devices. The network device obtains device or network-related parameters associated with the one or more devices and generates profiling vectors for each of the multiple users, that connects to the network using the one or more devices, to produce multiple profiling vectors. The network device clusters the multiple profiling vectors to identify cluster centers associated with a plurality of user groups, and determines first users of the multiple users for, or with, whom to perform certain actions or activities based on the first users' affinity with one or more of the plurality of user groups. The network device performs the certain actions or activities with respect to the determined first users.

Abstract: An application on a mobile device, in response to received partial queries from users, displays suggested results based upon the received partial query, allowing the user to select a suggested result without having to input the complete query. In order to ensure that suggested results can be provided to the user in a timely manner, the application determines an expected latency of a network connection of the mobile device by periodically measuring the latency of network requests and predicting an expected future latency based upon the measured latency values. Based upon the expected latency, the application may retrieve the suggested results from a server, or from a local cache storing results of previous queries by the users as well as popular results associated with a geographic area of the user, or some combination thereof.

Abstract: An application on a mobile device, in response to received partial queries from users, displays suggested results based upon the received partial query, allowing the user to select a suggested result without having to input the complete query. In order to ensure that suggested results can be provided to the user in a timely manner, the application determines an expected latency of a network connection of the mobile device by periodically measuring the latency of network requests and predicting an expected future latency based upon the measured latency values. Based upon the expected latency, the application may retrieve the suggested results from a server, or from a local cache storing results of previous queries by the users as well as popular results associated with a geographic area of the user, or some combination thereof.

Abstract: A positioning determination method using an improved RFID location tag is described the tag including an RFID controller; memory; a power management module; and an accelerometer. The position determination method including the steps of periodically polling the RFID tags for information; receiving information from a plurality of reference RFID tags at a known location; receiving information from the non reference RFID tags, the information including the tag id and sensor data; calculating for each non reference and referenced RFID tag a received signal strength indication; and calculating an initial position for each non reference RFID tag based on the received signal strength indications and the positions of the reference RFID tags.

Abstract: A positioning determination method using an improved RFID location tag is described the tag including an RFID controller; memory; a power management module; and an accelerometer. The position determination method including the steps of periodically polling the RFID tags for information; receiving information from a plurality of reference RFID tags at a known location; receiving information from the non reference RFID tags, the information including the tag id and sensor data; calculating for each non reference and referenced RFID tag a received signal strength indication; and calculating an initial position for each non reference RFID tag based on the received signal strength indications and the positions of the reference RFID tags.