摘要:
In some aspects, a system and method include receipt of a text file representation of an invoice associated with a supplier, receipt, from a database, of an invoice term associated with the supplier, determination, by a processor, of whether the invoice term is in the text file representation of the invoice. If is determined that the invoice term is in the text file representation of the invoice, an anchor term associated with the invoice term is determined. The invoice term and the anchor term are stored in a record associated with the supplier.
摘要:
Systems, methods and articles for determining anomalous user activity are disclosed. Data representing a transaction activity corresponding to a plurality of user transactions can be received and user transactions can be grouped according to types of user transactions. The transaction activity can be determined to be anomalous in relation to the grouped user transactions based on a predetermined parameter.
摘要:
A method and system utilizing one or more search terms corresponding to a search criteria is operable to search one or more data repositories of one or more modules. According to one implementation, one or more search strings may be inputted in a search screen. Each search string may correspond to a separate search criteria and may include one or more search terms. The search terms may be utilized to form a search table. A multiple value screen may be selectable from the search screen. The search terms are used to populate the one or more fields provided on the multiple value screen. The search terms may be added to, modified, or deleted in the multiple value screen. The search screen may be selectable from the multiple value screen, and any modification, deletion, or addition of the search terms may be updated in the search table and the search string.
摘要:
Systems, methods and articles for determining anomalous user activity are disclosed. Data representing a transaction activity corresponding to a plurality of user transactions can be received and user transactions can be grouped according to types of user transactions. The transaction activity can be determined to be anomalous in relation to the grouped user transactions based on a predetermined parameter.