Abstract: A method modifies how content is broadcast based on the tone and format of the content. One or more processors retrieve a set of rules that describe a tone and format for proposed content that is to be broadcast to an intended target, and determine whether the proposed content conforms to the set of rules. In response to determining that the proposed content does not conform to the set of rules, the processor(s) modify how the proposed content is broadcast to the intended target. The processor(s) generate an enriched content of the modified content by applying, to the modified content, content metatags that describe a content of the modified content, and then analyze the enriched content to calculate a trustworthiness index (TI) for the enriched content. The processors further modify how content is broadcast to the intended target based on the TI of the enriched content.

Abstract: A computer system may receive a first set of bundled information. The computer system may have a processor and a memory storing one or more natural language processing modules. The computer system, using a natural language processing module, may ingest the first set of bundled information. The computer system may generate a first set and a second set of categories. The computer system may generate one or more models. The computer system may receive a set of input characteristics. The computer system may select a model based on the input characteristics. The computer system may rank one or more correlations using the selected model. The computer system may output a display of the one or more correlations on a graphical user interface.

Abstract: A computer system may receive a first set of bundled information. The computer system may have a processor and a memory storing one or more natural language processing modules. The computer system, using a natural language processing module, may ingest the first set of bundled information. The computer system may generate a first set and a second set of categories. The computer system may generate one or more models. The computer system may receive a set of input characteristics. The computer system may select a model based on the input characteristics. The computer system may rank one or more correlations using the selected model. The computer system may output a display of the one or more correlations on a graphical user interface.

Abstract: A communication engine collects a first topic of a first user. The communication engine retrieves a message-aggregation from a content delivery repository. The message-aggregation includes a plurality of messages and a title. The message-aggregation is generated by a content provider before retrieval. The communication engine detects a relevant first message in the plurality of messages based on the first topic. The communication engine alters the message-aggregation such that the relevant first message is distinguished from the plurality of messages other than the first message. The alteration is based on the detected relevant first message. The communication engine also alters the title of the message-aggregation based on the detected relevant first message.

Abstract: A method modifies how content is broadcast based on the tone and format of the content. One or more processors retrieve a set of rules that describe a tone and format for proposed content that is to be broadcast to an intended target, and determine whether the proposed content conforms to the set of rules. In response to determining that the proposed content does not conform to the set of rules, the processor(s) modify how the proposed content is broadcast to the intended target. The processor(s) generate an enriched content of the modified content by applying, to the modified content, content metatags that describe a content of the modified content, and then analyze the enriched content to calculate a trustworthiness index (TI) for the enriched content. The processors further modify how content is broadcast to the intended target based on the TI of the enriched content.

Abstract: A method adjusts a broadcasting system according to properties of content being broadcast. One or more processors receive a proposed content that is designed to be a component of an electronic broadcast by a broadcast system. The processor(s) determine a broadcast analysis pattern (BAP) for the proposed content, where the BAP describes the proposed content and an intended target of the electronic broadcast. The processor(s) retrieve a set of rules that describe a tone and format for particular content that is broadcast to the intended target, and determine whether the proposed content conforms to the set of rules. In response to determining that the proposed content does not conform to the set of rules, the processor(s) adjust the broadcasting system, where adjusting the broadcasting system modifies how content is broadcast to the intended target.

Abstract: Systems and methods for monitoring and managing potable water installations (PWIs) systems are disclosed. In embodiments, a computer-implemented method comprises: receiving, by a computing device, monitoring data from a PWI via a network; generating, by the computing device, misery factor data for misery factors including availability of water, quality of water and hygiene of the PWI, wherein the misery factor data is based on the monitoring data; assigning, by the computing device, weights to the misery factor data for each of the misery factors; calculating, by the computing device, a misery index based on the misery factor data, wherein the misery index is a number indicative of conditions at the PWI; and generating, by the computing device, an alarm based on the misery data.

Abstract: A computer system may receive a first set of bundled information. The computer system may have a processor and a memory storing one or more natural language processing modules. The computer system, using a natural language processing module, may ingest the first set of bundled information. The computer system may generate a first set and a second set of categories. The computer system may generate one or more models. The computer system may receive a set of input characteristics. The computer system may select a model based on the input characteristics. The computer system may rank one or more correlations using the selected model. The computer system may output a display of the one or more correlations on a graphical user interface.

Abstract: A computer system may receive a first set of bundled information. The computer system may have a processor and a memory storing one or more natural language processing modules. The computer system, using a natural language processing module, may ingest the first set of bundled information. The computer system may generate a first set and a second set of categories. The computer system may generate one or more models. The computer system may receive a set of input characteristics. The computer system may select a model based on the input characteristics. The computer system may rank one or more correlations using the selected model. The computer system may output a display of the one or more correlations on a graphical user interface.

Abstract: A communication engine collects a first topic of a first user. The communication engine retrieves a message-aggregation from a content delivery repository. The message-aggregation includes a plurality of messages and a title. The message-aggregation is generated by a content provider before retrieval. The communication engine detects a relevant first message in the plurality of messages based on the first topic. The communication engine alters the message-aggregation such that the relevant first message is distinguished from the plurality of messages other than the first message. The alteration is based on the detected relevant first message. The communication engine also alters the title of the message-aggregation based on the detected relevant first message.

Abstract: A communication engine collects a first topic of a first user. The communication engine retrieves a message-aggregation from a content delivery repository. The message-aggregation includes a plurality of messages and a title. The message-aggregation is generated by a content provider before retrieval. The communication engine detects a relevant first message in the plurality of messages based on the first topic. The communication engine alters the message-aggregation such that the relevant first message is distinguished from the plurality of messages other than the first message. The alteration is based on the detected relevant first message. The communication engine also alters the title of the message-aggregation based on the detected relevant first message.

Abstract: A communication engine collects a first topic of a first user. The communication engine retrieves a message-aggregation from a content delivery repository. The message-aggregation includes a plurality of messages and a title. The message-aggregation is generated by a content provider before retrieval. The communication engine detects a relevant first message in the plurality of messages based on the first topic. The communication engine alters the message-aggregation such that the relevant first message is distinguished from the plurality of messages other than the first message. The alteration is based on the detected relevant first message. The communication engine also alters the title of the message-aggregation based on the detected relevant first message.

Abstract: In an approach to paraphrasing text, a computing device receives text as viewed by a user. The computing device determines whether a personalized dictionary is available, where the personalized dictionary includes a writing history of the first user. In response to determining the personalized dictionary is available, the computing device retrieves the personalized dictionary. The computing device determines, based, at least in part, on the personalized dictionary, whether the first user prefers paraphrasing of the received text. In response to determining the first user prefers paraphrasing of the received text, the computing device determines paraphrased text based on contents of the personalized dictionary. The computing device displays the paraphrased text to the first user.