Abstract: According to one embodiment, a method, computer system, and computer program product for utilizing a pricing engine is provided. The present invention may include analyzing pricing factors of one or more products in an online listing; recommending a best price proposal to list the one or more products based on the analyzed pricing factors; analyzing buyer factors of a potential buyer; and recalculating the best price proposal based on the analyzed buyer factors.

Abstract: Generation of pricing and promotions for personalized sale of an item includes receiving ordering data associated with an item from a user using an electronic shopping platform accessed via a user device. A failure of the user to complete a purchase order is determined using shopping cart activities of an ordering system. Based on a search pattern of the user received from the ordering system, a price of the item is identified as causing the determined failure of the user to complete the purchase order. Within a predefined time interval from the determined failure, a price range for the item is generated including a confidence score derived based on the search pattern of the user. Based on the confidence score of the generated price range exceeding a threshold, a final price recommendation for the item is generated and communicated to the user device.

Abstract: A method includes identifying a cluster of users with a plurality of devices, where each user from the cluster of users is associated with at least one device from the plurality of devices. The method also includes identifying an authorized user from the cluster of users to delegate role assignments to a remaining portion of the cluster of users and receiving, from the authorized user, a first role assignment for a first user from the remaining portion of the cluster of users. In response to receiving, from the first user, an audio command, the method also includes determining whether the first user is authorized to provide the audio command to the intelligent virtual assistant based on the first role assignment. In response to determining the first user is authorized to provide the audio command, the method also includes performing the audio command from the first user.

Abstract: A system and method are used to record and present a training video for a software component. The method displays the video recording. The video recording comprises: a display element of the software component, and first recorder activity data (FRAD) of recorder user interface (UI) input activity data (RUIIAD) at a FRAD time with video frame data of the video recording. The method further comprises receiving, during the displaying, viewer UI actions from a UI of the viewing device and converting them to viewer UI input activity data based on viewer interactions with the display element of the software component. Then, first viewer activity data (FVAD) is determined at a FVAD time of the video frame that corresponds to the FRAD, where the FRAD time and the FVAD time differ. Responsive to the determining, the method moves the video recording from the FVAD time to the FRAD time.

Abstract: A computer-implemented method for resolving a potential loss of sale, is disclosed. The computer-implemented method includes determining a potential lost sale and an item associated with the potential lost sale. The computer-implemented method further includes determining a reason for the potential lost sale of the item. The computer-implemented method further includes determining one or more substitute items for the item based, at least in part, on the determined reason for the potential lost sale of the item. The computer-implemented method further includes presenting the one or more determined substitute items to a user.

Abstract: A computer-implemented process for training a neural network includes the following operations. Return data received from a return channel is evaluated against a threshold. Based upon the threshold being satisfied, the return data is validated, and the return data is cognitive processed to generate a return insight. Using the neural network and based upon the return insight, a corrective action is generated. The neural network is trained using feedback generated based upon the corrective action. The threshold is then updated using the neural network.

Abstract: A computer implemented method converts an interest in an item into a set of purchasing options. A computer system detects the interest in the item viewed by a potential customer outside of a sales channel using real time user data from a user computing device. The computer system locates the item offered by a set of online sellers using an image of the item in response to detecting the interest in the item. The computer system determines a set of purchasing options to purchase the item. The computer system sends the set of purchasing options to purchase the item to the user computing device for presentation on the user computing device. According to other illustrative embodiments, a computer system and a computer program product for converting an interest in an item into a set of purchasing options are provided.

Abstract: A method, computer system, and a computer program product for enhancing a customer experience is provided. The present invention may include collecting data for a store visit. The present invention may include determining whether to offer the user one or more rewards based on the data collected. The present invention may include determining the one or more rewards to offer the user. The present invention may include presenting the one or more rewards to the user.

Abstract: An approach for optimizing storage on a local storage device. The approach identifies a stored or being stored on a user's local storage device. The approach extracts metadata from the media file. The approach searches the user-associated storage locations for a matching media file based on the metadata. If the approach locates the matching media file, then the approach, using artificial intelligence (AI), predicts if the local device storage should be optimized for the media file, then the approach, using AI, stores a link to the matching media file on the local device storage and removes the media file from the local device storage.

Abstract: Recommending commute options to a user based on a relevance of physical advertisements on the commute options to user's requirements includes capturing, by a computer, physical advertisements on possible commute options within a region, determining an item requirement of a user and correlating the captured physical advertisements on each possible commute option with the determined item requirement of the user, and determining a user's availability to look at the physical advertisements on each possible commute option between a starting point of a trip and a final point of the trip. A relevance score is then assigned to each of the captured physical advertisements on each possible commute option and the determined item requirement of the user, and based on the relevance score and the determined user's availability to look at the physical advertisements for each possible commute option, all possible commute options are sorted and communicated to a user device.

Abstract: A computer implemented method, apparatus, system, and computer program product for recommending item attributes. A computer system determines the item attributes in an item profile for an item offered by a seller on an item transaction platform. The computer system identifies interactions between the seller and a potential buyer regarding the item. The computer system determines a set of missing item attributes from the item profile based on the interactions between the seller and the potential buyer. The computer system recommends a set of actions for the set of missing item attributes identified to a seller of the item in a recommendation. The computer system performs a set of actions in the recommendation using the set of missing item attributes in response to a user input from the seller responding to the recommendation.

Abstract: A head mounted display device includes a frame with multiple tubes inside the frame. The tubes contain a number of speakers and valves. The valves can be actuated on demand, changing the air column length relative to the speakers. Based on an input sound, speakers can be selected and valves can be actuated to improve sound quality.

Abstract: A computer implemented method for automatically customizing electronic commerce includes analyzing information relevant to the user's purchasing preferences, determining the user's purchasing preferences based on the analysis of the relevant information, determining a shopping list, wherein the shopping list comprises one or more products the user wants to purchase and one or more indications of the user's purchasing preferences for each of the one or more products, generating one or more digital shopping carts based on the shopping list, comparing a product in at least one of the one or more digital shopping carts to a corresponding product and a corresponding purchasing preference on the shopping list, determining one or more preferred digital shopping carts based on the comparison, and displaying to the user the one or more preferred digital shopping carts.

Abstract: Embodiments herein disclose computer-implemented methods, computer program products and computer systems for context based online garage offering. The computer-implemented method may include receiving listing data from the seller users corresponding to items offered for sale, wherein the one or more seller users and one or more buyer users are registered with a web-based exchange platform based on user registration data; determining a seller context for the items based on the user registration data and the listing data; receiving historical item data for the items; determining disposal costs versus carry costs for the items based on the historical item data; determine potential buyers based on the listing data and potential buyer activity of the buyers; determining a buyer context based on the user registration data and the potential buyer activity; generating offer data for the items; and presenting the offer data to the seller users via a computing device user interface.

Abstract: In an approach, a processor receives a request to purchase an item from a retailer, where the request includes a location. A processor receives a request to purchase an item from a retailer, where the request includes location information associated with a buyer. A processor identifies that the item is unavailable from the retailer. A processor determines a plurality of users predicted to have a surplus quantity of the item beyond each respective user's estimated needs at a time of the request. A processor sends an offer to the plurality of users to transfer the item in accordance with the request. A processor, responsive to receiving an acceptance of the offer, selects at least one accepting user, of the plurality of users, based on geographic proximity to the location information. A processor coordinates fulfillment of the request by the at least one user.

Abstract: Pairing of multiple devices is initiated using a computer in an artificial intelligence (AI) ecosystem. A command is received at a computer to perform a user activity at a location which includes pairing a user device to a selectable device at the location. The context of the command is analyzed including a historical corpus regarding previous pairings and connection preferences. A device at the location is selected based on the analysis and the determining of the user activity. Pairing is automatically initiated for the user device to the selected device at the location based on the analysis of the context of the command. The automatic initiation includes adjusting settings on the user device based on the analysis of the context of the command. The user device is automatically paired to the selected device at the location to perform the user activity.

Abstract: An embodiment associates a user's post data that with a category from a predefined list of categories based on the post content. The embodiment analyzes, using machine learning, the post data for potentially sensitive content and generates a first sensitive data indicator identifying potentially sensitive information in the post data and an associated first confidence value. The embodiment generates explanatory data identifying a feature that contributed to the post data being identified as potentially sensitive, and generates a modified version of the post data that modifies the feature. The embodiment analyzes the modified post data for potentially sensitive content and generates a second sensitive data indicator and a second confidence value indicating that the post data is more likely to contain sensitive data than the modified post data. The embodiment alerts the user regarding the potentially sensitive data and recommends changing the post based on the modified feature value.

Abstract: Providing an Artificial Intelligence (AI) and Internet of Things (IoT) based system and method that predicts the chronological requirements for various components of the file-being-stored, and then takes an appropriate storage action on each component based on the predicted chronological requirements.

Abstract: A contact lens for application to a human eyeball capable of emitting ultrasonic pressure waves from a plurality of piezoelectric transducers to mitigate the effects of airborne eye irritants and infectious microorganisms. The piezoelectric transducers converts mechanical energy applied upon the contact lens from the eyelid as the eyelid blinks and/or winks into electrical energy to be used for emitting ultrasonic pressure waves from the piezoelectric transducers. The ultrasonic pressure waves destroy airborne microorganisms near the contact lens. A photodiode onboard the contact lens indicates when the eyelid is not closed in order to limit or prevent emission of ultrasonic pressure waves from the piezoelectric transducers while the eyelid is closed. An antenna onboard the contact lens receives information from augmented reality glasses or other computing devices.

Abstract: A processor may receive user data associated with a voice conversation having one or more participating users. The processor may analyze the user data for voice content associated with the voice conversation and the one or more participating users. The processor may determine a security policy associated with the voice conversation. The processor may identify one or more permission rules from the security policy associated with the voice conversation. The processor may dynamically execute the one or more permission rules to a portion of the voice content associated with at least one participating user. Dynamically executing the one or more permission rules may include modifying the portion of the voice content.