Abstract: A method is disclosed. The method includes a relationship server receiving a discovery service request from a client computer, the relationship server comparing metadata provided in the discovery service request against a database and a crawler retrieving updated metadata from a commerce server for if the metadata provided in the discovery service request does not match the metadata stored in the database column.

Abstract: A method is disclosed. The method includes a relationship server receiving a discovery service request from a client computer, the relationship server comparing metadata provided in the discovery service request against a database and a crawler retrieving updated metadata from a commerce server for if the metadata provided in the discovery service request does not match the metadata stored in the database column.

Abstract: A method is disclosed. The method includes a relationship server receiving a discovery service request from a client computer, the relationship server comparing metadata provided in the discovery service request against a database and a crawler retrieving updated metadata from a commerce server for if the metadata provided in the discovery service request does not match the metadata stored in the database column.

Abstract: A method is disclosed. The method includes a relationship server receiving a discovery service request from a client computer, the relationship server comparing metadata provided in the discovery service request against a database and a crawler retrieving updated metadata from a commerce server for if the metadata provided in the discovery service request does not match the metadata stored in the database column.

Abstract: To implement a multi-touch attribution model, a conversion event resulting from user activity is programmatically detected. A set of events that precede the conversion event is identified. Respective events of the set occur on respective websites. The conversion event is attributed to multiple websites of the respective websites.

Abstract: A memory management module operates to receive a query that identifies a set of data of a logical data structure. The logical data structure is stored with memory resources that are provided on multiple service-level tiers of a network environment, where the multiple service-level tiers may include at least a first tier of memory resources and a second tier of memory resources. From the query, a subset of data is determined that is stored with the second tier of memory resources. The memory management module responds to detecting the condition or event by causing transfer of the subset of data items from the second tier of memory resources to the first tier of memory resources.

Abstract: To implement a multi-touch attribution model, a conversion event resulting from user activity is programmatically detected. A set of events that precede the conversion event is identified. Respective events of the set occur on respective websites. The conversion event is attributed to multiple websites of the respective websites.

Abstract: A method is disclosed including a client accessing a cache for a value of an object based on an object identification (ID), initiating a request to a cache loader if the cache does not include a value for the object, the cache loader performing a lookup in an object table for the object ID corresponding to the object, the cache loader retrieving a vector of execution context IDs, from an execution context table that correspond to the object IDs looked up in the object table and the cache loader performing an execution context lookup in an execution context table for every retrieved execution context ID in the vector to retrieve object IDs from an object vector.

Abstract: A method is disclosed including a client accessing a cache for a value of an object based on an object identification (ID), initiating a request to a cache loader if the cache does not include a value for the object, the cache loader performing a lookup in an object table for the object ID corresponding to the object, the cache loader retrieving a vector of execution context IDs, from an execution context table that correspond to the object IDs looked up in the object table and the cache loader performing an execution context lookup in an execution context table for every retrieved execution context ID in the vector to retrieve object IDs from an object vector.

Abstract: To implement a multi-touch attribution model, a conversion event resulting from user activity is programmatically detected. A set of events that precede the conversion event is identified. Respective events of the set occur on respective websites. The conversion event is attributed to multiple websites of the respective websites.

Abstract: A computer system that includes at least one processor, a first storage resource, and a second storage resource maintains a count of key events. The system determines that the count is not significant and, in response, stores data associated with the key in the second storage resource. The system subsequently can determine when the count has become significant and, in response, stores the data associated with the key in the first storage resource.

Abstract: A method is disclosed including a client accessing a cache for a value of an object based on an object identification (ID), initiating a request to a cache loader if the cache does not include a value for the object, the cache loader performing a lookup in an object table for the object ID corresponding to the object, the cache loader retrieving a vector of execution context IDs, from an execution context table that correspond to the object IDs looked up in the object table and the cache loader performing an execution context lookup in an execution context table for every retrieved execution context ID in the vector to retrieve object IDs from an object vector.

Abstract: A method is disclosed including a client accessing a cache for a value of an object based on an object identification (ID), initiating a request to a cache loader if the cache does not include a value for the object, the cache loader performing a lookup in an object table for the object ID corresponding to the object, the cache loader retrieving a vector of execution context IDs, from an execution context table that correspond to the object IDs looked up in the object table and the cache loader performing an execution context lookup in an execution context table for every retrieved execution context ID in the vector to retrieve object IDs from an object vector.

Abstract: Systems and methods are described for performing the dynamic generation of correlation scores between arbitrary objects. When a behavioral event is recorded, that is to say when an end user interacts with multiple objects, relationships between objects are created. These relationships are maintained as a list. When a request for correlated items is requested based upon a seed object, a list of correlated items is dynamically created through the generation of a pivot set and a scoring algorithm to compute the list of correlated items.

Abstract: Systems and methods are described for performing the dynamic generation of correlation scores between arbitrary objects. When a behavioral event is recorded, that is to say when an end user interacts with multiple objects, relationships between objects are created. These relationships are maintained as a list. When a request for correlated items is requested based upon a seed object, a list of correlated items is dynamically created through the generation of a pivot set and a scoring algorithm to compute the list of correlated items.

Abstract: A method is disclosed including a client accessing a cache for a value of an object based on an object identification (ID), initiating a request to a cache loader if the cache does not include a value for the object, the cache loader performing a lookup in an object table for the object ID corresponding to the object, the cache loader retrieving a vector of execution context IDs, from an execution context table that correspond to the object IDs looked up in the object table and the cache loader performing an execution context lookup in an execution context table for every retrieved execution context ID in the vector to retrieve object IDs from an object vector.

Abstract: A method is disclosed including a client accessing a cache for a value of an object based on an object identification (ID), initiating a request to a cache loader if the cache does not include a value for the object, the cache loader performing a lookup in an object table for the object ID corresponding to the object, the cache loader retrieving a vector of execution context IDs, from an execution context table that correspond to the object IDs looked up in the object table and the cache loader performing an execution context lookup in an execution context table for every retrieved execution context ID in the vector to retrieve object IDs from an object vector.

Abstract: When an end user opens an e-mail the user's e-mail client requests the image content based on the image tag from a recommendation platform and sends an identification to the recommendation platform as part of the image URL. The user ID or seed item is looked up in the recommendation platform database and associated behavioral data and any applicable rules to generate content for the e-mail and the content is then displayed in the e-mail as an image. When the image is engaged, a request is sent to the recommendation platform that references the user or request identifier and a logical location in the image where the click occurred, the image location is looked up along with the user or request identifier to present the correct page or content for the user.

Abstract: Systems and methods are described for performing the dynamic generation of correlation scores between arbitrary objects. When a behavioral event is recorded, that is to say when an end user interacts with multiple objects, relationships between objects are created. These relationships are maintained as a list. When a request for correlated items is requested based upon a seed object, a list of correlated items is dynamically created through the generation of a pivot set and a scoring algorithm to compute the list of correlated items.

Abstract: A relationship server tracks end-user interactions across multiple web sites and generates recommendations. The web sites observe relationships established by end-user interactions. If end-users provide the same personally identifiable information to multiple web sites, the sites generate the same unique identifier for those end-users. The web sites send messages to the relationship server that reference the end-users using the identifiers and describe the relationships observed for the end-users. The relationship server receives messages from multiple web sites and canonicalizes them to produce an efficient representation of the relationships. Upon receiving a message requesting a recommendation based on an item, the relationship server performs collaborative filtering using the relationship data to identify a list of items to recommend. The relationship server sends the recommendations to the requesting entity and the recommendations are presented to the end-user.