Abstract: A machine learning system for forecasting demand implements an improved process using event streams for predicting the impact that events in the geographic area surrounding an establishment have on demand forecasts for the establishment. A range of distances from the establishment can be determined and divided up into different distances. Event streams can be generated from the events by grouping the events into combinations of event attributes, such as event category and the distance of the event from the establishment. The event streams can be provided as inputs along with demand data for computing demand forecasts that account for increased or decreased traffic patterns in the geographic area surrounding the event. The event streams can be filtered based on the magnitude of the impact the events have on the demand for the products and/or services of the establishment before, during and after the event takes place.

Abstract: The embodiments in this disclosure include a system for receiving search requests for one or more items from a client device having access to a local database that stores primary catalogs containing items of contracted entities. If the items are not found in the primary catalogs, the system may be configured to execute an API for processing the search request by routing the search request to a proxy vendor computer in a cloud network. The cloud network may be configured to store vendor master records for one or more non-contracted entities. The proxy vendor computer can conduct a text search of secondary catalogs associated with non-contracted entities, and can transmit search results to the client device for the requested items. The items may correspond to one or more vendor master records associated with a non-contracted entity and may have a matching entry in one or more of the secondary catalogs.

Abstract: Disclosed is a machine learning system for adapting demand forecasts to varying time slots or intervals within a forecast day, for example when an organization's hours of operation change. The system computes a demand curve for the demand data and thereafter modifies the demand curve using curve shaping operations to adapt the demand curve to new or different time slots. Demand forecasts for the new or different time slots can thereafter be computed using values interpolated from the modified demand curve. In one embodiment, curve shaping operations are performed in a manner in which the peak values for the time slots in the demand forecast are preserved. Peak detection and segmentation operations may also be used in combination with the curve shaping to further adapt the demand forecasts.

Abstract: Disclosed is a machine learning system with date alignment features for improved demand forecasting for products and/or services. The system includes an appliance for more accurately aligning days and weeks between years, including adapting to holidays and special days, in order to ascertain the date in a previous year that most closely aligns with the date in the future for which the forecast is sought. The corresponding day in one or more previous years can then be computed and demand data associated therewith can be retrieved from data storage to be used in forecasting demand on the forecast date. The most closely aligned day from a previous year can be selected such that the aligned day is positioned appropriately within the calendar week and year and the aligned day falls within a week that is positioned appropriately within the calendar month (i.e., first week, last week or middle-month weeks).

Abstract: Disclosed is a system for forecasting demand for goods and/or services. In at least certain embodiments the system is configurable to select a machine learning model from among multiple different machine learning models for forecasting demand for a dataset that may be continually being updated over time. The models available to the system are each based on different machine learning algorithms (e.g., linear regression, gradient boosting, neural network, etc.) as well as several variations for each algorithm available to the system. The system can monitor changes in the datasets, changes in accuracy of the machine learning results, and external factors, and based thereon, determine whether to initiate a model reselection process or a model retraining process. Each machine learning model can be evaluated against each dataset and can select the best model for the dataset.

Abstract: The embodiments in this disclosure include a system for receiving search requests for one or more items from a client device having access to a local database that stores primary catalogs containing items of contracted entities. If the items are not found in the primary catalogs, the system may be configured to execute an API for processing the search request by routing the search request to a proxy vendor computer in a cloud network. The cloud network may be configured to store vendor master records for one or more non-contracted entities. The proxy vendor computer can conduct a text search of secondary catalogs associated with non-contracted entities, and can transmit search results to the client device for the requested items. The items may correspond to one or more vendor master records associated with a non-contracted entity and may have a matching entry in one or more of the secondary catalogs.

Abstract: Embodiments for methods, systems and apparatuses of a commerce network for completing a commercial transaction are disclosed. One computer-method includes receiving, by one or more commerce network servers, a buyer-initiated demand for fulfillment of the commercial transaction, identifying suppliers to satisfy the buyer-initiated demand based on buyer policies and supplier characteristics, requesting quotes from the identified suppliers, receiving quotes from the identified suppliers, evaluating and selecting, by the one or more commerce network servers, one or more of the received quotes, wherein evaluating and selecting the one or more of the received quote comprises applying evaluating criteria to the received quotes, wherein the evaluation criteria includes applying a weighted combination of a plurality of evaluating factors, and facilitating presentation of the one or more selected quotes to the buyer.

Abstract: The embodiments in this disclosure include a system for receiving search requests for one or more items from a client device having access to a local database that stores primary catalogs containing items of contracted entities. If the items are not found in the primary catalogs, the system may be configured to execute an API for processing the search request by routing the search request to a proxy vendor computer in a cloud network. The cloud network may be configured to store vendor master records for one or more non-contracted entities. The proxy vendor computer can conduct a text search of secondary catalogs associated with non-contracted entities, and can transmit search results to the client device for the requested items. The items may correspond to one or more vendor master records associated with a non-contracted entity and may have a matching entry in one or more of the secondary catalogs.

Abstract: In one embodiment, a method comprises: receiving a procurement request for an item; determining whether the item is in a contracted catalog; processing the procurement request per a first set of procurement rules if the item is in the contract catalog; and processing the procurement request per a second set of procurement rules if the item is not in the contract catalog. The second set of procurement rules include procurement rules that are in the first set of procurement rules. In some embodiments, the method further comprises tracking the procurement requests for items not in the contract catalog. In some embodiments, the method further comprises analyzing the tracked procurement requests; and adding a tracked item to the contracted catalog based on the tracked procurement requests meeting a first set of criteria.

Abstract: Embodiments for methods, systems and apparatuses of a commerce network for completing a commercial transaction are disclosed. One computer-method includes receiving, by one or more commerce network servers, a buyer-initiated demand for fulfillment of the commercial transaction, identifying suppliers to satisfy the buyer-initiated demand based on buyer policies and supplier characteristics, requesting quotes from the identified suppliers, receiving quotes from the identified suppliers, evaluating and selecting, by the one or more commerce network servers, one or more of the received quotes, wherein evaluating and selecting the one or more of the received quote comprises applying evaluating criteria to the received quotes, wherein the evaluation criteria includes applying a weighted combination of a plurality of evaluating factors, and facilitating presentation of the one or more selected quotes to the buyer.

Abstract: Embodiments of methods, systems and apparatus for integrating commerce networks are disclosed. One method includes receiving a commercial transaction request associated with a business process from a member of the second commerce network, to conduct commerce with a member of the first commerce network, wherein the request includes a second commerce network associated identifier, confirming that the member of the second commerce network is a user of the second commerce network based on the second commerce network associated identifier, enabling the member of the second commerce network to join the first commerce network upon confirmation that the member of the second commerce network is a user of the second commerce network, and allowing the member of the second commerce network to conduct commerce on the first commerce network after enabling the member of the second commerce network.

Abstract: Enabling a supplier is disclosed. An indication of a transaction associated with a business process between a buyer and a supplier is received. A supplier enablement action is initiated in response to receiving the indication. The supplier enablement action is associated with enabling the supplier to join a supplier network.

Abstract: Embodiments of methods, systems and apparatus for a buyer/supplier network aiding supplier enablement through creation of a requisition between a buyer and a supplier are disclosed. One method includes receiving, by the buyer/supplier network, a collaboration request for information about a good or service being purchased by a buyer. At least one supplier is identified from an approved supplier list that has the requested information. An account is created for each of the identified suppliers on the buyer/supplier network, and an invitation is sent to each of the suppliers to join the buyer/supplier network. Each of the invited suppliers is allowed to log into the buyer/supplier network through the invitation, and address the request for information.

Abstract: Enabling a supplier is disclosed. An indication of a transaction associated with a business process between a buyer and a supplier is received. A supplier enablement action is initiated in response to receiving the indication. The supplier enablement action is associated with enabling the supplier to join a supplier network.