Abstract: Embodiments of the present invention disclose a method, computer program product, and system for modifying a display of a product to emphasize feature that might cause a consumer to return a product. Receiving a new product that a consumer would like to view on a web browser on a consumer computing device and identifying at least one return feature about the new product that might cause the consumer to return the new product after it was purchased. Determining a return probability for the new product and determining, that the return probability is greater than or equal to a threshold value. Modifying a default product display for the new product to emphasize the identified at least one return feature of the new product.

Abstract: The exemplary embodiments disclose a method, a computer program product, and a computer system for determining the context of media. The exemplary embodiments may include a user consuming media, collecting data of the media, extracting one or more features from the collected data, and determining a media context based on the extracted one or more features and one or more models.

Abstract: A computer-implemented method, computer system, and computer program product for a container deployment simulation. The method may include performing a container deployment simulation. The method may include detecting a container deployment simulation error. In response to detecting the container deployment simulation error, the method may include providing one or more recommendations to a user. In response to receiving an acceptance of the recommendation from the user, the method may include implementing the recommendation. In response to receiving a rejection of the recommendation from the user, the method may include receiving a user recommendation. The method may include implementing the user recommendation and performing the container deployment simulation. The one or more recommendations may have a weight value. The weight value of the one or more recommendations may be increased when the user accepts the one or more recommendations or reduced when the user rejects the one or more recommendations.

Abstract: A method can include obtaining access code data corresponding to an access code transmitted to a user device. The method can further include monitoring the user device. The method can further include determining, based on the monitoring, that the access code is shared. The method can further include initiating, in response to the determining that the access code is shared, an invalidation of the access code.

Abstract: A system for manipulating a 3D object for a computing device is provided. A computer device identifies one or more sensors worn by a user, wherein the one or more sensors track the user's hand and finger movements. The computing device monitors during production of a three dimensional (3D) object, the one or more sensors for modification to a holographic projection representing the 3D object, wherein the user's hand and finger movements modify the holographic projection representing the 3D object. A computing device identifies a modification to the 3D object represented by the holographic projection. A computing device generates a modification request based, at least in part, on the identified modification. The computing device updates production of the 3D object, based, at least in part, on the modification request.

Abstract: The exemplary embodiments disclose a method, a computer program product, and a computer system for responding to communications based on context. The exemplary embodiments may include a user receiving a contextual communication, collecting data relating to an environment of the user, extracting one or more features from the collected data, and generating one or more responses to the received contextual communication based on the extracted one or more features and one or more models.

Abstract: A method, system, and computer program product for simulating potential consequences and possible solutions due to a release of stored energy using augmented reality. The method may include aggregating IoT feeds from devices in a surrounding area. The method may also include calculating amounts of stored energy in the surrounding area based on the IoT feeds. The method may also include predicting contextual situations that could result due to a release of the stored energy in the surrounding area. The method may also include determining one or more consequences for each of the contextual situations. The method may also include calculating a degree of severity of the one or more consequences for each contextual situation. The method may also include determining one or more proposed solutions based on the degree of severity. The method may also include transmitting a recommendation of at least one proposed solution for implementation.

Abstract: Aspects of the present invention disclose a method for managing aggregated comments of a forwarded media based on the sentiments of the forwarded media and relevance to a user. The method includes one or more processors identifying a user based at least in part on information provided by the user. The method further includes accessing user activity data utilizing the information provided by the user. The method further includes generating a first profile corresponding to the user based at least in part on the user activity data. The method further includes determining one or more preferences of the user based at least in part on the generated first profile. The method further includes identifying segments of textual data of forwarded media the user receives based at least in part on the preferences of the user, wherein the textual data corresponds to a comment associated with the forwarded media.

Abstract: A method comprises displaying a plurality of items to a user on a first page on a display screen of an electronic device. Each item of the plurality of items displayed on the first page is classified according to whether an item is of interest to the user viewing the display screen. A correlation factor between the user and each item classified as of interest to the user is determined. The method also includes, for at least the first one of the plurality of items determined to have a correlation factor above a predetermined threshold, identifying detailed information about a first one of the plurality of items. The identified detailed information about a first one of the plurality of items is automatically displayed. The identified detailed information is displayed without receiving an input indicating a selection of a first one of the plurality of items from a hand-operated input device.

Abstract: A component-based review system for generating a digital recommendation is provided. A computing device monitors for one or more consumer-based reviews. A computing device identifies one or more commercial products or services associated with the one or more consumer-based reviews. A computing device generates a digital recommendation associated with the one or more consumer-based reviews.

Abstract: A computer-implemented method for detecting oligopoly in a data processing system, the method comprising: pretending to be a first competing AI pricing engine for a business provider; querying, by a second competing AI pricing engine, the first competing AI pricing engine for a first price; providing, by the first competing AI pricing engine, a plurality of first prices to the second competing AI pricing engine; querying, by the first competing AI pricing engine, the second competing AI pricing engine for a second price; providing, by the second competing AI pricing engine, a plurality of second prices to the second competing AI pricing engine; identifying, by the processor, a correlation between the plurality of first prices and the plurality of second prices using a machine learning technique; and flagging, by the processor, the second competing AI pricing engine, as a possible oligopoly participant.

Abstract: A computer-implemented method for detecting oligopoly in a data processing system, the method comprising: pretending to be a first competing AI pricing engine for a business provider; querying, by a second competing AI pricing engine, the first competing AI pricing engine for a first price; providing, by the first competing AI pricing engine, a plurality of first prices to the second competing AI pricing engine; querying, by the first competing AI pricing engine, the second competing AI pricing engine for a second price; providing, by the second competing AI pricing engine, a plurality of second prices to the second competing AI pricing engine; identifying, by the processor, a correlation between the plurality of first prices and the plurality of second prices using a machine learning technique; and flagging, by the processor, the second competing AI pricing engine, as a possible oligopoly participant.

Abstract: A method for directional based commands includes responsive to initializing an augmented reality device associated with a user, establishing a field of view for the augmented reality device associated with the user. The method establishes boundaries for a directional command area, where the directional command area includes a plurality of devices configurable to receive commands from the augmented reality device associated with the user. The method receives a first command performable by at least two devices from the plurality of devices and receives orientation data from the augmented reality device associated with the user. The method determines a first device from the plurality of devices for performing the first command based at least on the orientation data and the field of view of view for the augmented reality device associated with the user and sends the first command to the first device.

Abstract: Cognitive enablement can include detecting sensor-generated signals received from one or more network-configured sensors, the sensor-generated signals corresponding to physical movement of an audience member during a presentation by a presenter. The sensor-generated signals can be converted to vectorized data structures for inputting to a classification model generated with machine learning. The physical movement can be classified as a prelude to a likely audience interaction, the classifying performed by the classification model based on the vectorized data structures. In response to the classifying, an audience member attribute associated with the audience member can be determined. An audience interaction can be predicted based on the audience member attribute using a prediction model generated with machine learning. A predictive alert corresponding to the predicted audience interaction can be generated.

Abstract: Cognitive enablement can include detecting sensor-generated signals received from one or more network-configured sensors, the sensor-generated signals corresponding to physical movement of an audience member during a presentation by a presenter. The sensor-generated signals can be converted to vectorized data structures for inputting to a classification model generated with machine learning. The physical movement can be classified as a prelude to a likely audience interaction, the classifying performed by the classification model based on the vectorized data structures. In response to the classifying, an audience member attribute associated with the audience member can be determined. An audience interaction can be predicted based on the audience member attribute using a prediction model generated with machine learning. A predictive alert corresponding to the predicted audience interaction can be generated.

Abstract: The exemplary embodiments disclose a system and method, a computer program product, and a computer system for determining the context of calls and providing a user interface to a user. The exemplary embodiments may include collecting data from the call, extracting one or more features from the collected data, determining a context of the call based on applying one or more models to the extracted one or more features, and providing a user with a user interface.

Abstract: Using a forecasting model, a timeline of future activities is forecasted. Using a constraints analysis model, a set of profile inputs is analyzed to determine a context of a first period in the forecasted timeline. Using a context extraction model, a first notification from a set of notifications is analyzed to determine a context of the first notification. A degree of correspondence is computed between the context of the first period and the context of the first notification. When the degree of correspondence is at least a threshold degree of correspondence, the first notification is scheduled for presentation during the first period regardless of a time of arrival of the first notification.

Abstract: A method includes providing a smart contact lens including an array of beamforming microphones, wherein the smart contact lens is worn by a user and the array of beamforming microphones receive sound from different directions, determining a gaze direction of the user, filter the sound received by the array of beamforming microphones based on the gaze direction of the user to determine filtered sound, and output the filtered sound via a bone conduction hearing device.

Abstract: A method, system and computer-usable medium are disclosed for deriving a region in which brand awareness is supported. Shoppers are detected in the region where brand awareness is to be supported, where such shoppers can be brand ambassadors. Items used for brand awareness are determined as to the brand ambassadors. Items are offered to the brand ambassadors, where the items can promote brand awareness.

Abstract: An approach for identifying mitigation solution based on critical situations is disclosed. The approach includes detecting one or more critical situations associated within a structure and detecting one or more location of one or more users in the structure. The approach retrieves a user-knowledge corpus based on one or more smart IoT devices or from existing database. Furthermore, the approach retrieves a critical situation knowledge corpus from various servers and creates risk mitigation action plans to address the one or more critical situations. The approach selects an optimal plan, by leveraging machine learning through combinatorial optimization technique, from the existing risk mitigation action plans and executing the optimal plan.