Abstract: A method is provided. The method includes one or more of obtaining client device data including a plurality of facts from a client device, each fact including an entity, an observation, and an object, performing one or more directed searches, each for obtaining one or more entities, observations, or objects not present in the client device data, incorporating the entities, the observations, and the objects from the one or more directed searches into the plurality of facts, comparing the plurality of facts to categorized historical data, and determining one or more closest matches between the plurality of facts and the categorized historical data.

Abstract: A method is provided. The method includes one or more of obtaining client device data including a plurality of facts from a client device, limiting the client device data according to selection criteria, comparing, using a neural network, the limited client device data to categorized historical data, determining, using the neural network, one or more closest matches between the limited client device data and the categorized historical data, and selecting, on the client device, content of interest from the one or more closest matches. Each fact includes an entity, an observation, and an object. Limiting the client device data includes reviewing the entity, observation, and object for each fact and one or more of eliminating facts having an entity, observation, or object that does not meet the selection criteria and removing data from entities, observations, or objects that uniquely identifies a user associated with the client device.

Abstract: A method is provided. The method includes one or more of obtaining client device data including a plurality of facts from a client device, limiting the client device data according to selection criteria, comparing, using a neural network, the limited client device data to categorized historical data, determining, using the neural network, one or more closest matches between the limited client device data and the categorized historical data, and selecting, on the client device, content of interest from the one or more closest matches. Each fact includes an entity, an observation, and an object. Limiting the client device data includes reviewing the entity, observation, and object for each fact and one or more of eliminating facts having an entity, observation, or object that does not meet the selection criteria and removing data from entities, observations, or objects that uniquely identifies a user associated with the client device.

Abstract: A method is provided. The method includes one or more of obtaining client device data including a plurality of facts from a client device, limiting the client device data according to selection criteria, comparing the limited client device data to categorized historical data, determining one or more closest matches between the limited client device data and the categorized historical data, selecting, on the client device, content of interest from the one or more closest matches, and incorporating the content of interest into the categorized historical data. Each fact includes an entity, an observation, and an object.

Abstract: A method is provided. The method includes one or more of obtaining client device data including a plurality of facts from a client device, limiting the client device data according to selection criteria, comparing the limited client device data to categorized historical data, determining one or more closest matches between the limited client device data and the categorized historical data, selecting, on the client device, content of interest from the one or more closest matches, and incorporating the content of interest into the categorized historical data. Each fact includes an entity, an observation, and an object.