Abstract: A method of providing examples to a computerized conversation agent includes associating one or more triplets of two concepts and a relationship therebetween with an intent related to a query. The triplet is embedded in a knowledge graph and the concepts in the knowledge graph are mapped to the intent. A call log is scanned for examples of the intent based on the concepts in the knowledge graph and the examples are mapped to the intent.

Abstract: A method of providing examples to a computerized conversation agent includes associating one or more triplets of two concepts and a relationship therebetween with an intent related to a query. The triplet is embedded in a knowledge graph and the concepts in the knowledge graph are mapped to the intent. A call log is scanned for examples of the intent based on the concepts in the knowledge graph and the examples are mapped to the intent.

Abstract: Embodiments provide for dialog based speech recognition by clustering a plurality of nodes comprising a dialog tree into at least a first cluster and a second cluster; creating a first dataset of natural language sentences for the first cluster and a second dataset of natural language sentences for the second cluster; generating a first specialized language model (LM) associated with the first cluster based on the first dataset; and generating a second specialized LM associated with the second cluster based on the second dataset, wherein the first specialized LM is different from the second specialized LM.

Abstract: A determination regarding whether to intervene in a dialog to provide system-initiated assistive information involves monitoring a dialog between at least two participants and capturing data from a dialog environment containing at least one of the participants. The captured data represent the content of the dialog and physiological data for one or more participants. Assistive information relevant to the dialog and participants is identified, and the captured data are used to determine an intervention index of delivering the assistive information to one or more participants during the dialog. This intervention index is then used to determine whether or not to intervene in the dialog to deliver the assistive information to one or more participants.

Abstract: Embodiments provide for dialog based speech recognition by clustering a plurality of nodes comprising a dialog tree into at least a first cluster and a second cluster; creating a first dataset of natural language sentences for the first cluster and a second dataset of natural language sentences for the second cluster; generating a first specialized language model (LM) associated with the first cluster based on the first dataset; and generating a second specialized LM associated with the second cluster based on the second dataset, wherein the first specialized LM is different from the second specialized LM.

Abstract: Embodiments are directed to a computer-implemented method that includes receiving, at a triggering system, input data about an environment. Machine learning (ML) algorithms extract features from the input data and analyze relationships among and between the features to generate user-interaction-readiness model of person-A's readiness to participate in a human interaction with other persons in the environment. The ML algorithms to apply real-world data about person-A to the user-interaction-readiness model to generate a first classification output comprising data representing person-A's readiness to participate in a human interaction with other persons in the environment. Based at least in part on a determination that person-A and another person(s) in the environment are interaction candidates, the triggering system triggers the initiation of human interaction strategies configured to facilitate human interactions between person-A and the previously identified another person(s) in the environment.

Abstract: Embodiments are directed to a computer-implemented method that includes receiving, at a triggering system, input data about an environment. Machine learning (ML) algorithms extract features from the input data and analyze relationships among and between the features to generate user-interaction-readiness model of person-A's readiness to participate in a human interaction with other persons in the environment. The ML algorithms to apply real-world data about person-A to the user-interaction-readiness model to generate a first classification output comprising data representing person-A's readiness to participate in a human interaction with other persons in the environment. Based at least in part on a determination that person-A and another person(s) in the environment are interaction candidates, the triggering system triggers the initiation of human interaction strategies configured to facilitate human interactions between person-A and the previously identified another person(s) in the environment.

Abstract: A determination regarding whether to intervene in a dialog to provide system-initiated assistive information involves monitoring a dialog between at least two participants and capturing data from a dialog environment containing at least one of the participants. The captured data represent the content of the dialog and physiological data for one or more participants. Assistive information relevant to the dialog and participants is identified, and the captured data are used to determine an intervention index of delivering the assistive information to one or more participants during the dialog. This intervention index is then used to determine whether or not to intervene in the dialog to deliver the assistive information to one or more participants.

Abstract: Embodiments of the invention provide techniques which utilize crowdsourced reports of environmental conditions to predict and/or prevent disease outbreaks. In one aspect, a method comprises receiving one or more crowdsourced reports about one or more environmental conditions; inferring one or more input parameters for at least one disease outbreak model based at least in part on the one or more crowdsourced reports; applying the at least one disease outbreak model to at least the one or more inferred parameters to predict one or more characteristics of at least one potential disease outbreak associated with the reported one or more environmental conditions; and, based at least in part on the predicted one or more characteristics, implementing one or more corrective actions to mitigate the at least one potential disease outbreak.

Abstract: A determination regarding whether to intervene in a dialog to provide system-initiated assistive information involves monitoring a dialog between at least two participants and capturing data from a dialog environment containing at least one of the participants. The captured data represent the content of the dialog and physiological data for one or more participants. Assistive information relevant to the dialog and participants is identified, and the captured data are used to determine an intervention index of delivering the assistive information to one or more participants during the dialog. This intervention index is then used to determine whether or not to intervene in the dialog to deliver the assistive information to one or more participants.

Abstract: A determination regarding whether to intervene in a dialog to provide system-initiated assistive information involves monitoring a dialog between at least two participants and capturing data from a dialog environment containing at least one of the participants. The captured data represent the content of the dialog and physiological data for one or more participants. Assistive information relevant to the dialog and participants is identified, and the captured data are used to determine an intervention index of delivering the assistive information to one or more participants during the dialog. This intervention index is then used to determine whether or not to intervene in the dialog to deliver the assistive information to one or more participants.

Abstract: A method, system and computer program product for servicing media content. In one embodiment, the media content is processed by having each of a group of services process increments of the media content, one increment at a time; and the order in which the services process these increments is orchestrated to process all of the media content in accordance with a defined procedure. In one embodiment, the increments of the media content are passed, one increment after another, to at least a plurality of the services in a defined order. In an embodiment, each time one of the plurality of services passes one of the increments of the media content to a subsequent one of the services in the defined order, the one of the plurality of services requests another increment of the media content from a preceding one of the services in the defined order.

Abstract: A determination regarding whether to intervene in a dialog to provide system-initiated assistive information involves monitoring a dialog between at least two participants and capturing data from a dialog environment containing at least one of the participants. The captured data represent the content of the dialog and physiological data for one or more participants. Assistive information relevant to the dialog and participants is identified, and the captured data are used to determine an intervention index of delivering the assistive information to one or more participants during the dialog. This intervention index is then used to determine whether or not to intervene in the dialog to deliver the assistive information to one or more participants.

Abstract: A determination regarding whether to intervene in a dialog to provide system-initiated assistive information involves monitoring a dialog between at least two participants and capturing data from a dialog environment containing at least one of the participants. The captured data represent the content of the dialog and physiological data for one or more participants. Assistive information relevant to the dialog and participants is identified, and the captured data are used to determine an intervention index of delivering the assistive information to one or more participants during the dialog. This intervention index is then used to determine whether or not to intervene in the dialog to deliver the assistive information to one or more participants.

Abstract: Aspects relate to computer implemented methods, systems, and processes to automatically generate audio-based display indicia of media content including receiving, by a processor, a plurality of media content categories including at least one feature, receiving a plurality of categorized speech recognition algorithms, each speech recognition algorithm being associated with a respective one or more of the plurality of media content categories, determining a media content category of a current media content based on at least one feature of the current media content, selecting one speech recognition algorithm from the plurality of categorized speech recognition algorithms based on the determination of the media content category of the current media content, and applying the selected speech recognition algorithm to the current media content.

Abstract: A system to measure effectiveness of displayed content includes a video processing service configured to receive and process a stream of video images captured by one or more video cameras, a display application service configured to produce display content to be displayed on one or more display monitors and to capture user interactions with the displayed content, and a display effectiveness service configured to correlate data received from the video processing service and the display application service and generate a display effectiveness measurement that is a measure of an effectiveness of the displayed content for specific periods of time.

Abstract: A system to measure effectiveness of displayed content includes a video processing service configured to receive and process a stream of video images captured by one or more video cameras, a display application service configured to produce display content to be displayed on one or more display monitors and to capture user interactions with the displayed content, and a display effectiveness service configured to correlate data received from the video processing service and the display application service and generate a display effectiveness measurement that is a measure of an effectiveness of the displayed content for specific periods of time.

Abstract: A method, system and computer program product for servicing media content. In one embodiment, the media content is processed by having each of a group of services process increments of the media content, one increment at a time; and the order in which the services process these increments is orchestrated to process all of the media content in accordance with a defined procedure. In one embodiment, the increments of the media content are passed, one increment after another, to at least a plurality of the services in a defined order. In an embodiment, each time one of the plurality of services passes one of the increments of the media content to a subsequent one of the services in the defined order, the one of the plurality of services requests another increment of the media content from a preceding one of the services in the defined order.

Abstract: A method, system and computer program product for servicing media content. In one embodiment, the media content is processed by having each of a group of services process increments of the media content, one increment at a time; and the order in which the services process these increments is orchestrated to process all of the media content in accordance with a defined procedure. In one embodiment, the increments of the media content are passed, one increment after another, to at least a plurality of the services in a defined order. In an embodiment, each time one of the plurality of services passes one of the increments of the media content to a subsequent one of the services in the defined order, the one of the plurality of services requests another increment of the media content from a preceding one of the services in the defined order.

Abstract: An information processing system, a computer readable storage medium, and a method for identifying review material can include collecting assessment data at a server from a plurality of client devices for subject matter in a course, analyzing collectively the assessment data from the plurality of client devices, and based on the analyzing, identifying a deficient subset of topics. The method can further include selecting review material based on the deficient subset of topics identified and sending the review material or a signal representative of the review material to the plurality of client devices which can include presenting the review material to the plurality of client devices. The method can include presenting the review material to each of the plurality of client devices in a format based on a student profile corresponding to each client device in the plurality of client devices.