Abstract: The CLOUD SERVICE FACILITATOR APPARATUSES, METHODS AND SYSTEMS (“CSF”) transforms user purchase requests, refund requests, and product/service replacement requests via CSF components into transaction records, refunds, and replacement products/services outputs. The CSF may receive a consumer purchase request for a cloud service from a merchant. In response to the request, the CSF may generate a unique record key for the purchase and may transmit the unique record key to the merchant. The CSF may further receive additional transaction information and the unique record key from the merchant. In response to the received information and the unique key, the CSF may provide additional service to the merchant or the consumer.

Abstract: Methods for controlling genetic learning for predictive models using predefined strategies may include, for each of a plurality of agents, selecting a type of predictive model. A strategy may be selected from predefined strategies. Candidate genomes may be generated and may include a plurality of genes. Each gene may be associated with a feature of the agent predictive model. A fit of each candidate genome to the agent strategy may be determined. A candidate genome may be selected based on the fit. For each of a plurality of epochs, a plurality of training iterations may be performed for each agent. A fitness of each agent predictive model may be determined. A subset of agents with a highest fitness may be determined. For each agent of the subset, at least one new agent may be generated. The genomes of the new agents may be merged with some genomes of the subset.

Abstract: The MERCHANT-CONSUMER BRIDGING PLATFORM APPARATUSES, METHODS AND SYSTEMS (“MCB-Platform”) various activity requests (e.g., transaction request, merchant information update request, offer issuance request, etc.) via MCB-Platform components into transaction records and merchant database updates outputs.

Abstract: The MULTI-SOURCE, MULTI-DIMENSIONAL, CROSS-ENTITY, MULTIMEDIA ANALYTICAL MODEL SHARING DATABASE PLATFORM APPARATUSES, METHODS AND SYSTEMS (“AMSDB”) transform data aggregated from various computer resources using AMSDB components into updated entity profiles and/or social graphs. In one implementation, the AMSDB aggregates data records including search results, purchase transaction data, service usage data, service enrollment data, and social data. The AMSDB identifies data field types within the data records and their associated data values. From the data field types and their associated data values, the AMSDB identifies an entity. The AMSDB generates correlations of the entity to other entities identifiable from the data field types and their associated data values. The AMSDB also associates attributes to the entity by drawing inferences related to the entity from the data field types and their associated data values.

Abstract: The Multi-Source, Multi-Dimensional, Cross-Entity, Multimedia Centralized Personal Information Database Platform Apparatuses, Methods And Systems (“CPDB”) transform data aggregated from various computer resources using CPDB components into updated entity profiles and/or social graphs. Using generated correlations and associated attributes, the CPDB generates an updated profile and social graph of the entity. The CPDB provides the updated profile and social graph for an automated web form filling request.

Abstract: The MULTI-SOURCE, MULTI-DIMENSIONAL, CROSS-ENTITY, MULTIMEDIA MERCHANT ANALYTICS DATABASE PLATFORM APPARATUSES, METHODS AND SYSTEMS (“MDB”) transform data aggregated from various computer resources using MDB components into updated entity profiles and/or social graphs. In one implementation, the MDB aggregates data records including search results, purchase transaction data, service usage data, service enrollment data, and social data. The MDB identifies data field types within the data records and their associated data values. From the data field types and their associated data values, the MDB identifies an entity. The MDB generates correlations of the entity to other entities identifiable from the data field types and their associated data values. The MDB also associates attributes to the entity by drawing inferences related to the entity from the data field types and their associated data values.

Abstract: The MERCHANT-CONSUMER BRIDGING PLATFORM APPARATUSES, METHODS AND SYSTEMS (“MCB-Platform”) various activity requests (e.g., transaction request, merchant information update request, offer issuance request, etc.) via MCB-Platform components into transaction records and merchant database updates outputs.

Abstract: The MERCHANT-CONSUMER BRIDGING PLATFORM APPARATUSES, METHODS AND SYSTEMS (“MCB-Platform”) various activity requests (e.g., transaction request, merchant information update request, offer issuance request, etc.) via MCB-Platform components into transaction records and merchant database updates outputs.

Abstract: The MULTI-SOURCE, MULTI-DIMENSIONAL, CROSS-ENTITY, MULTIMEDIA ANALYTICAL MODEL SHARING DATABASE PLATFORM APPARATUSES, METHODS AND SYSTEMS (“AMSDB”) transform data aggregated from various computer resources using AMSDB components into updated entity profiles and/or social graphs. In one implementation, the AMSDB aggregates data records including search results, purchase transaction data, service usage data, service enrollment data, and social data. The AMSDB identifies data field types within the data records and their associated data values. From the data field types and their associated data values, the AMSDB identifies an entity. The AMSDB generates correlations of the entity to other entities identifiable from the data field types and their associated data values. The AMSDB also associates attributes to the entity by drawing inferences related to the entity from the data field types and their associated data values.

Abstract: The CLOUD SERVICE FACILITATOR APPARATUSES, METHODS AND SYSTEMS (“CSF”) transforms user purchase requests, refund requests, and product/service replacement requests via CSF components into transaction records, refunds, and replacement products/services outputs. The CSF may receive a consumer purchase request for a cloud service from a merchant. In response to the request, the CSF may generate a unique record key for the purchase and may transmit the unique record key to the merchant. The CSF may further receive additional transaction information and the unique record key from the merchant. In response to the received information and the unique key, the CSF may provide additional service to the merchant or the consumer.

Abstract: The MULTI-SOURCE, MULTI-DIMENSIONAL, CROSS-ENTITY, MULTIMEDIA ANALYTICAL MODEL SHARING DATABASE PLATFORM APPARATUSES, METHODS AND SYSTEMS (“AMSDB”) transform data aggregated from various computer resources using AMSDB components into updated entity profiles and/or social graphs. In one implementation, the AMSDB aggregates data records including search results, purchase transaction data, service usage data, service enrollment data, and social data. The AMSDB identifies data field types within the data records and their associated data values. From the data field types and their associated data values, the AMSDB identifies an entity. The AMSDB generates correlations of the entity to other entities identifiable from the data field types and their associated data values. The AMSDB also associates attributes to the entity by drawing inferences related to the entity from the data field types and their associated data values.

Abstract: The CLOUD SERVICE FACILITATOR APPARATUSES, METHODS AND SYSTEMS (“CSF”) transforms user purchase requests, refund requests, and product/service replacement requests via CSF components into transaction records, refunds, and replacement products/services outputs. The CSF may receive a consumer purchase request for a cloud service from a merchant. In response to the request, the CSF may generate a unique record key for the purchase and may transmit the unique record key to the merchant. The CSF may further receive additional transaction information and the unique record key from the merchant. In response to the received information and the unique key, the CSF may provide additional service to the merchant or the consumer.

Abstract: The MULTI-SOURCE, MULTI-DIMENSIONAL, CROSS-ENTITY, MULTIMEDIA MERCHANT ANALYTICS DATABASE PLATFORM APPARATUSES, METHODS AND SYSTEMS (“MDB”) transform data aggregated from various computer resources using MDB components into updated entity profiles and/or social graphs. In one implementation, the MDB aggregates data records including search results, purchase transaction data, service usage data, service enrollment data, and social data. The MDB identifies data field types within the data records and their associated data values. From the data field types and their associated data values, the MDB identifies an entity. The MDB generates correlations of the entity to other entities identifiable from the data field types and their associated data values. The MDB also associates attributes to the entity by drawing inferences related to the entity from the data field types and their associated data values.

Abstract: The MULTI-SOURCE, MULTI-DIMENSIONAL, CROSS-ENTITY, MULTIMEDIA MERCHANT ANALYTICS DATABASE PLATFORM APPARATUSES, METHODS AND SYSTEMS (“MDB”) transform data aggregated from various computer resources using MDB components into updated entity profiles and/or social graphs. In one implementation, the MDB aggregates data records including search results, purchase transaction data, service usage data, service enrollment data, and social data. The MDB identifies data field types within the data records and their associated data values. From the data field types and their associated data values, the MDB identifies an entity. The MDB generates correlations of the entity to other entities identifiable from the data field types and their associated data values. The MDB also associates attributes to the entity by drawing inferences related to the entity from the data field types and their associated data values.

Abstract: An entity may store various levels of sensitive and personal data in a secure computing environment. The entity may create permission rules which allow the data to be shared or not shared depending on the circumstances and situation. As an entity such as a human moves through life, the entity may be in touch with numerous electronic devices that act like sensors. The entity may share a token which may allow a sensor or operator of the sensor to access various levels of the sensitive data stored in the secure computing environment.

Abstract: THE MULTI-SOURCE, MULTI-DIMENSIONAL, CROSS-ENTITY, MULTIMEDIA CENTRALIZED PERSONAL INFORMATION DATABASE PLATFORM APPARATUSES, METHODS AND SYSTEMS (“CPDB”) transform data aggregated from various computer resources using CPDB components into updated entity profiles and/or social graphs. In one implementation, the CPDB aggregates data records including search results, purchase transaction data, service usage data, service enrollment data, and social data. The CPDB identifies data field types within the data records and their associated data values. From the data field types and their associated data values, the CPDB identifies an entity. The CPDB generates correlations of the entity to other entities identifiable from the data field types and their associated data values. The CPDB also associates attributes to the entity by drawing inferences related to the entity from the data field types and their associated data values.

Abstract: THE MULTI-SOURCE, MULTI-DIMENSIONAL, CROSS-ENTITY, MULTIMEDIA CENTRALIZED PERSONAL INFORMATION DATABASE PLATFORM APPARATUSES, METHODS AND SYSTEMS (“CPDB”) transform data aggregated from various computer resources using CPDB components into updated entity profiles and/or social graphs. In one implementation, the CPDB aggregates data records including search results, purchase transaction data, service usage data, service enrollment data, and social data. The CPDB identifies data field types within the data records and their associated data values. From the data field types and their associated data values, the CPDB identifies an entity. The CPDB generates correlations of the entity to other entities identifiable from the data field types and their associated data values. The CPDB also associates attributes to the entity by drawing inferences related to the entity from the data field types and their associated data values.

Abstract: The MULTI-SOURCE, MULTI-DIMENSIONAL, CROSS-ENTITY, MULTIMEDIA MERCHANT ANALYTICS DATABASE PLATFORM APPARATUSES, METHODS AND SYSTEMS (“MDB”) transform data aggregated from various computer resources using MDB components into updated entity profiles and/or social graphs. In one implementation, the MDB aggregates data records including search results, purchase transaction data, service usage data, service enrollment data, and social data. The MDB identifies data field types within the data records and their associated data values. From the data field types and their associated data values, the MDB identifies an entity. The MDB generates correlations of the entity to other entities identifiable from the data field types and their associated data values. The MDB also associates attributes to the entity by drawing inferences related to the entity from the data field types and their associated data values.

Abstract: The MULTI-SOURCE, MULTI-DIMENSIONAL, CROSS-ENTITY, MULTIMEDIA ENCRYPTMATICS DATABASE PLATFORM APPARATUSES, METHODS AND SYSTEMS (“EXDB”) transform data aggregated from various computer resources using EXDB components into updated entity profiles and/or social graphs. In one implementation, the EXDB aggregates data records including search results, purchase transaction data, service usage data, service enrollment data, and social data. The EXDB identifies data field types within the data records and their associated data values. From the data field types and their associated data values, the EXDB identifies an entity. The EXDB generates correlations of the entity to other entities identifiable from the data field types and their associated data values. The EXDB also associates attributes to the entity by drawing inferences related to the entity from the data field types and their associated data values.

Abstract: The MULTI-SOURCE, MULTI-DIMENSIONAL, CROSS-ENTITY, MULTIMEDIA ANALYTICAL MODEL SHARING DATABASE PLATFORM APPARATUSES, METHODS AND SYSTEMS (“AMSDB”) transform data aggregated from various computer resources using AMSDB components into updated entity profiles and/or social graphs. In one implementation, the AMSDB aggregates data records including search results, purchase transaction data, service usage data, service enrollment data, and social data. The AMSDB identifies data field types within the data records and their associated data values. From the data field types and their associated data values, the AMSDB identifies an entity. The AMSDB generates correlations of the entity to other entities identifiable from the data field types and their associated data values. The AMSDB also associates attributes to the entity by drawing inferences related to the entity from the data field types and their associated data values.