Abstract: In one embodiment, a computer-implemented method includes receiving a query. A target confidence level is established for the query, the target confidence level representing a requested level of accuracy for a result of the query. At least one individual confidence level is assigned to each of a plurality of analytics engines. One or more analytics engines are queried based on the query. A group of the analytics engines are selected, by a computer processor, where the analytics engines in the selected group have query responses to the query that are deemed to be similar to one another, and where the selection of the selected group is at least partially based on the target confidence level. The query responses from the selected group of analytics engines are summarized into a final result, where the final result is an answer to the query.

Abstract: In one embodiment, a computer-implemented method includes receiving a query. A target confidence level is established for the query, the target confidence level representing a requested level of accuracy for a result of the query. At least one individual confidence level is assigned to each of a plurality of analytics engines. One or more analytics engines are queried based on the query. A group of the analytics engines are selected, by a computer processor, where the analytics engines in the selected group have query responses to the query that are deemed to be similar to one another, and where the selection of the selected group is at least partially based on the target confidence level. The query responses from the selected group of analytics engines are summarized into a final result, where the final result is an answer to the query.

Abstract: A technique is provided for capturing browsing history of a webpage. A processor receives a webpage from a server, determines that a trigger associated with a user is fulfilled, and captures a page of the webpage responsive to the trigger associated with the user being fulfilled.

Abstract: In one embodiment, a computer-implemented method includes receiving a query. A target confidence level is established for the query, the target confidence level representing a requested level of accuracy for a result of the query. At least one individual confidence level is assigned to each of a plurality of analytics engines. One or more analytics engines are queried based on the query. A group of the analytics engines are selected, by a computer processor, where the analytics engines in the selected group have query responses to the query that are deemed to be similar to one another, and where the selection of the selected group is at least partially based on the target confidence level. The query responses from the selected group of analytics engines are summarized into a final result, where the final result is an answer to the query.

Abstract: In one embodiment, a computer-implemented method includes receiving a query. A target confidence level is established for the query, the target confidence level representing a requested level of accuracy for a result of the query. At least one individual confidence level is assigned to each of a plurality of analytics engines. One or more analytics engines are queried based on the query. A group of the analytics engines are selected, by a computer processor, where the analytics engines in the selected group have query responses to the query that are deemed to be similar to one another, and where the selection of the selected group is at least partially based on the target confidence level. The query responses from the selected group of analytics engines are summarized into a final result, where the final result is an answer to the query.

Abstract: According to an exemplary embodiment of this disclosure, a computer-implemented method includes capturing a plurality of images from a presentation. Each of the plurality of images is associated with a unique identifier. The unique identifiers are transmitted to one or more remote audience modules. The plurality of images are then transmitted to the audience modules. With a computer processor, a first image from the plurality of images is identified as a next active image. Indications are received from the one or more of the audience modules that the next active image has been received. The audience modules are instructed to update their displays from a current active image to the next active image, after the indications are received.

Abstract: According to an exemplary embodiment of this disclosure, a computer-implemented method includes capturing a plurality of images from a presentation. Each of the plurality of images is associated with a unique identifier. The unique identifiers are transmitted to one or more remote audience modules. The plurality of images are then transmitted to the audience modules. With a computer processor, a first image from the plurality of images is identified as a next active image. Indications are received from the one or more of the audience modules that the next active image has been received. The audience modules are instructed to update their displays from a current active image to the next active image, after the indications are received.

Abstract: A technique is provided for capturing browsing history of a webpage. A processor receives a webpage from a server, determines that a trigger associated with a user is fulfilled, and captures a page of the webpage responsive to the trigger associated with the user being fulfilled.