Abstract: A system and method for providing personalized recommendations or promotional information to consumers based upon a recommendation algorithm selected from a number of recommendation algorithms, by matching personal contextual information of each consumer to detailed contexts in which each recommendation algorithm exhibits optimal performance with regard to particular business performance measures.

Abstract: A system and method for providing personalized recommendations or promotional information to consumers based upon a recommendation algorithm selected from a number of recommendation algorithms, by matching personal contextual information of each consumer to detailed contexts in which each recommendation algorithm exhibits optimal performance with regard to particular business performance measures.

Abstract: A system and method for providing personalized recommendations or promotional information to consumers based upon a recommendation algorithm selected from a number of recommendation algorithms, by matching personal contextual information of each consumer to detailed contexts in which each recommendation algorithm exhibits optimal performance with regard to particular business performance measures.

Abstract: A method and system for emergent data processing are described. A system having one or more servers operable to handle retail data can receive content including customer data and product data. The content can be normalized and stored into a hyper-graph structure in the servers. The system can be used to select a portion of the hyper-graph structure based on a particular customer and to generate a recommendation for the particular customer based on the content in that portion of the hyper-graph structure. The system can also generate personal catalogs based on the information in the hyper-graph structure. The system can perform competitive analysis between products from different sources and include the results in the recommendations. Moreover, the system can perform a vertical analysis of consumable products to provide recommendations for tools or products that can be used in connection with the consumable products.

Abstract: A method and system for emergent data processing are described. A system having one or more servers operable to handle retail data can receive content including customer data and product data. The content can be normalized and stored into a hyper-graph structure in the servers. The system can be used to select a portion of the hyper-graph structure based on a particular customer and to generate a recommendation for the particular customer based on the content in that portion of the hyper-graph structure. The system can also generate personal catalogs based on the information in the hyper-graph structure. The system can perform competitive analysis between products from different sources and include the results in the recommendations. Moreover, the system can perform a vertical analysis of consumable products to provide recommendations for tools or products that can be used in connection with the consumable products.

Abstract: A system and method for providing personalized recommendations or promotional information to consumers based upon a recommendation algorithm selected from a number of recommendation algorithms, by matching personal contextual information of each consumer to detailed contexts in which each recommendation algorithm exhibits optimal performance with regard to particular business performance measures.

Abstract: An online social networking system for conducting commerce utilizes a grid environment, a widget architecture including a widget operating system, and semantic integration technologies to provide personalized bundling of products and services tied to an individual's life, emergent marketplaces that support collaboratively-based product and service development, merchandising, and recommendations, emergent user experiences, emergent gaming, emergent behavior predictions, collaborative discover, i.e., social searching, and content and/or people voyeurism. These features are achieved through the use of various techniques including emergent programming, emergent widget processing, emergent computations, emergent applications, widget composition, data integration and exchange, complex system management, security graphs, trust/reputation management, intersecting graphs, database sharding, use of fractal graphs (which may be thinned and expanded), and content mashups.

Abstract: An online social networking system for conducting commerce utilizes a grid environment, a widget architecture including a widget operating system, and semantic integration technologies to provide personalized bundling of products and services tied to an individual's life, emergent marketplaces that support collaboratively-based product and service development, merchandising, and recommendations, emergent user experiences, emergent gaming, emergent behavior predictions, collaborative discovery, i.e., social searching, and content and/or people voyeurism. These features are achieved through the use of various techniques including emergent programming, emergent widget processing, emergent computations, emergent applications, widget composition, data integration and exchange, complex system management, security graphs, trust/reputation management, intersecting graphs, database sharding, use of fractal graphs (which may be thinned and expanded), and content mashups.

Abstract: A system and method for providing personalized recommendations or promotional information to consumers based upon a recommendation algorithm selected from a number of recommendation algorithms, by matching personal contextual information of each consumer to detailed contexts in which each recommendation algorithm exhibits optimal performance.

Abstract: A system and method for providing personalized recommendations or promotional information to consumers based upon a recommendation algorithm selected from a number of recommendation algorithms, by matching personal contextual information of each consumer to detailed contexts in which each recommendation algorithm exhibits optimal performance with regard to particular business performance measures.

Abstract: A/B testing methods, apparatus, systems and presentations of A/B testing results are disclosed. An A/B testing method may include presenting a first version and second version under test to first and second groups of customers. The method may further include collecting, during a first test period, data based on responses to the first and second versions under test, and determining, based on data collected during the first test period, a probability representative of a likelihood that the second version outperforms the first version. The method may also include calculating an estimate for a second test period over which additional data regarding responses to the first and second version is to be collected before the likelihood that the second version outperforms the first version has a predetermined relationship to a target probability.

Abstract: A method and system for emergent data processing are described. A system having one or more servers operable to handle retail data can receive content including customer data and product data. The content can be normalized and stored into a hyper-graph structure in the servers. The system can be used to select a portion of the hyper-graph structure based on a particular customer and to generate a recommendation for the particular customer based on the content in that portion of the hyper-graph structure. The system can also generate personal catalogs based on the information in the hyper-graph structure. The system can perform competitive analysis between products from different sources and include the results in the recommendations. Moreover, the system can perform a vertical analysis of consumable products to provide recommendations for tools or products that can be used in connection with the consumable products.

Abstract: An online social networking system for conducting commerce utilizes a grid environment, a widget architecture including a widget operating system, and semantic integration technologies to provide personalized bundling of products and services tied to an individual's life, emergent marketplaces that support collaboratively-based product and service development, merchandising, and recommendations, emergent user experiences, emergent gaming, emergent behavior predictions, collaborative discovery, i.e., social searching, and content and/or people voyeurism. These features are achieved through the use of various techniques including emergent programming, emergent widget processing, emergent computations, emergent applications, widget composition, data integration and exchange, complex system management, security graphs, trust/reputation management, intersecting graphs, database sharding, use of fractal graphs (which may be thinned and expanded), and content mashups.