Abstract: A method of dynamically rendering cognitive contacts that includes: identifying transitory contacts of interest to a user of a mobile device in various contexts; identifying various contexts applicable to the user; sorting the transitory contacts of interest into transitory contact types; mapping the various contexts to the transitory contact types into a mapping table; deriving a present context pertaining to a user of the mobile device; querying the mapping table for transitory contact types applicable to the present context; dynamically rendering the applicable transitory contact types to the user in a transitory contacts screen on the mobile device; and responsive to the user selecting one of the applicable transitory contact types, displaying the transitory contacts of interest in the transitory contacts screen on the mobile device corresponding to the transitory contact type.

Abstract: A method of dynamically rendering cognitive contacts that includes: identifying transitory contacts of interest to a user of a mobile device in various contexts; identifying various contexts applicable to the user; sorting the transitory contacts of interest into transitory contact types; mapping the various contexts to the transitory contact types into a mapping table; deriving a present context pertaining to a user of the mobile device; querying the mapping table for transitory contact types applicable to the present context; dynamically rendering the applicable transitory contact types to the user in a transitory contacts screen on the mobile device; and responsive to the user selecting one of the applicable transitory contact types, displaying the transitory contacts of interest in the transitory contacts screen on the mobile device corresponding to the transitory contact type.

Abstract: A system for cross-domain adaptation includes an analysis module, a set configuration module, a set multiplexer, a scalable bloom filter, a mapping module, and an aggregation module. The cross-domain adaptation system may allow for bloom filter adaptation across industries and domains with minimal increases in necessary hardware and consequentially minimal increases in power consumption and cost of area. A method for multi-domain adaptation in datasets includes performing multi-domain semantic analysis on a set of data, providing two complementary domain adaptive sets, processing the complementary domain adaptive sets to provide a multi-fractal representation of the dataset, processing the multi-fractal representation of the dataset with a scalable bloom filter to provide two filtered domain adaptive sets, providing a bijective holomorphic map of the filtered domain adaptive sets, and processing the bijective holomorphic map to provide multi-domain insight aggregator output.

Abstract: Generating a social business insight is provided. An analysis parameter is selected. The analysis parameter represents a characteristic of a plurality of entities. A first data stream is retrieved. The first data stream is associated with a first entity of the plurality of entities and includes data from at least a CRM platform, a media platform, or a company asset database. A second data stream is retrieved. The second data stream is associated with a second entity of the plurality if entities and includes data from the media platform. A fractal analysis is performed based on the first data stream, the second data stream, and the analysis parameter. A fractal map is generated, where the fractal map depicts a relationship between the first data stream and the second data stream.

Abstract: A system for cross-domain adaptation includes an analysis module, a set configuration module, a set multiplexer, a scalable bloom filter, a mapping module, and an aggregation module. The cross-domain adaptation system may allow for bloom filter adaptation across industries and domains with minimal increases in necessary hardware and consequentially minimal increases in power consumption and cost of area. A method for multi-domain adaptation in datasets includes performing multi-domain semantic analysis on a set of data, providing two complementary domain adaptive sets, processing the complementary domain adaptive sets to provide a multi-fractal representation of the dataset, processing the multi-fractal representation of the dataset with a scalable bloom filter to provide two filtered domain adaptive sets, providing a bijective holomorphic map of the filtered domain adaptive sets, and processing the bijective holomorphic map to provide multi-domain insight aggregator output.

Abstract: Generating a social business insight is provided. An analysis parameter is selected. The analysis parameter represents a characteristic of a plurality of entities. A first data stream is retrieved. The first data stream is associated with a first entity of the plurality of entities and includes data from at least a CRM platform, a media platform, or a company asset database. A second data stream is retrieved. The second data stream is associated with a second entity of the plurality if entities and includes data from the media platform. A fractal analysis is performed based on the first data stream, the second data stream, and the analysis parameter. A fractal map is generated, where the fractal map depicts a relationship between the first data stream and the second data stream.