Abstract: Computer-implemented event detection includes obtaining, at one or more processors, multimedia data including multiple frames of video data and corresponding audio data. The processor(s) process the multiple frames to detect at least one object and to track the object(s) between two or more of the frames. The processor(s) generate sonification audio data representing a position of the object(s) in the two or more frames, movement of the object(s), or both the position and the movement of object(s). The processor(s) generate combined audio data including the audio data and the sonification audio data. The processor(s) generate one or more feature vectors representing the combined audio data and provide the feature vector(s) as input to a trained event classifier to detect an event represented in the multimedia data.

Abstract: A computer-implemented method for executing a composition of analytical models. In one embodiment, the computer-implemented method creates analytical model composition definitions for a plurality of analytical models. The computer-implemented method receives analytical model definitions and an analytical model composition. The computer-implemented method binds the analytical model composition to the analytical model definitions. The computer-implemented method deploys the analytical model composition using the analytical model composition definitions. The computer-implemented method executes the analytical model composition and returns a result of the analytical model composition.

Abstract: An automated leveling system for maintaining a level of a surface, comprising a surface traveling device and a leveling module attached to the surface traveling device. The leveling module comprises a depression detector arm assembly, at least one computing device, and a level-sensing detector. The level-sensing detector senses a level of a surface as the surface traveling device operates across the surface. The level-sensing detector moves across the surface according to the operation of the surface traveling device, and transmits a depression reporting signal to the computing device. The depression reporting signal indicates the presence of a depression in the surface if the level-sensing detector contacts a depression in the surface over a depression threshold.

Abstract: A method includes activating a first object detector and a second object detector. The first object detector is operable to detect a first type of object in a set of image frames, and the second object detector is operable to detect a second type of object in the set of image frames. The method also includes activating a first set of attribute classifiers and a second set of attribute classifiers. The method also includes generating first statistics for the first object detector and second statistics for the second object detector. The method also includes modifying activation of at least the second set of attribute classifiers based on a comparison of the first statistics and the second statistics.

Abstract: Creating an animated pictogram includes: generating a set of images depicting a weather forecast for a first location at different times according to a set of depiction rules and combining the set of images in chronological order according to a set of transition rules.

Abstract: A method includes determining, by a controller, characteristics of a hosting digital composition, wherein the digital composition hosts a digital advertisement. The method also includes dynamically modifying at least one characteristic of the digital advertisement based at least on the determined characteristics of the hosting digital composition to create a modified digital advertisement. The modifying the at least one characteristic of the digital advertisement configures the digital advertisement to be visually and/or semantically integrated within the hosting digital composition. The method also includes displaying the modified digital advertisement within the hosting digital composition.

Abstract: Provided are techniques for optimized deployment of analytic models in an edge topology. A description of a multi-tiered edge topology with a plurality of nodes, a multimedia stream analytics composition, and performance objectives are received, where the multimedia stream analytics composition includes tasks that use analytic models. The analytic models are optimized and clustered to form clusters of optimized analytic models. A representative optimized analytic model is selected from each of the clusters. A configuration recommendation is determined that indicates deployment of the tasks and of each selected representative optimized analytic model on the plurality of nodes to meet the performance objectives. One or more workflows are generated from the configuration recommendation and executed on the plurality of nodes to generate output for the multimedia stream analytics composition.

Abstract: A method, system, and computer program product for automated collection of training data and training object detection models is provided. The method generates a set of reference images for a first set of products. Based on the set of reference images, the method identifies a subset of products within an image stream. Based on the subset of products, a second set of products is determined within the image stream. The method identifies a set of product gaps based on the subset of products and the second set of products. The method generates a product detection model based on the set of reference images, the subset of products, the second set of products, and the product gaps.

Abstract: In an approach for efficient data processing in a mesh network of computing devices, a processor receives data to be processed in the mesh network. A processor distributes a set of computational units to a set of computing devices in the mesh network. A processor creates a computational plan to construct a computational pipeline of the set of computational units. The computational plan considers cost and performance trade-offs by considering limitation of hardware resources, processing speed, accuracy and application requirements. A processor executes the computational plan by sending data to assigned computational units.

Abstract: A chatbot answer database can be generated from a question and answer document. A question/answer processor can receive a document that includes questions and answers. A set of entities can be determined from the answers in the document. A set of triplets can be constructed from the answers, and stored in a chatbot database. For each answer, the question/answer processor can determine text for slots of the triplet based on the entities extracted from the answer. The triplet can be stored as a tree structure in a database of tree structures associated with the document. A chatbot can receive questions, and provide answers based on the database of tree structures associated with the document.

Abstract: A website navigation system has an analysis system which receives a request for an Internet web page from a client device. The analysis system receives web page data associated with the web page from the Internet and performs a data analysis process to organize the web page data for use in a virtual conversation with the user in order to present the web page in an audible format. The analysis system identifies separate elements of the web page from the web page data and extracts information from the separate elements based on the web page data. The analysis system groups the separate elements into categories based on the extracted information and sorts the groups of separate elements based on usage statistics. The analysis system then generates a prompt for being output to the user by the client device as audible output based on the sorted groups of separate elements.

Abstract: Provided are techniques for optimized deployment of analytic models in an edge topology. A description of a multi-tiered edge topology with a plurality of nodes, a multimedia stream analytics composition, and performance objectives are received, where the multimedia stream analytics composition includes tasks that use analytic models. The analytic models are optimized and clustered to form clusters of optimized analytic models. A representative optimized analytic model is selected from each of the clusters. A configuration recommendation is determined that indicates deployment of the tasks and of each selected representative optimized analytic model on the plurality of nodes to meet the performance objectives. One or more workflows are generated from the configuration recommendation and executed on the plurality of nodes to generate output for the multimedia stream analytics composition.

Abstract: A method, apparatus and program product utilize an automated educational tool to generate or modify one or more multiple choice questions in a question set in connection with tracking a user's attention state to dynamically vary the difficulty of a user assessment performed by the automated educational tool and thereby encourage the user to pay greater attention to the material being presented to the user.

Abstract: A system for entity-level clarification in conversation services includes a memory having instructions therein. The system also includes at least one processor in communication with the memory. The at least one processor is configured to execute the instructions to receive a conversation services training example set, build an entity usage map using the conversation services training example set, receive a user utterance, and, responsive to a reception of the user utterance, generate a clarification response using the entity usage map. The at least one processor is also configured to execute the instructions to provide the clarification response to a user.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for predicting a crowdedness of a location. In the example embodiment, a computer receives a location and defines a geofence around the location. In addition, the computer collects current feature data of users within the geofence and predicts a crowdedness of the location based on inputting the current feature data into a model.

Abstract: A method includes receiving, by a first device of a transportation provider, a device ID of a particular device of a user and purchase information regarding a purchase, by the user, of one or more goods or services. The method includes sending, by the first device, the device ID of the particular user device to a central server. The method includes receiving, by the first device from the central server, information regarding the particular user device. The method includes determining, by the first device, a selected transportation vehicle based on the purchase information and the information regarding the particular user device. The method includes sending, by the first device, a vehicle ID of the selected transportation vehicle to the central server. The method includes providing a transportation service to the user using the particular user device and the selected transportation vehicle.

Abstract: A life-logging system is configured to register a plurality of cameras and a plurality of users to a life-logging network. The life-logging system receives a plurality of camera profiles associated with the plurality of cameras and a user profile associated with a user. The life-logging system determines location information associated with the user and identifies a camera of the plurality of cameras for capturing an image of the user based on the plurality of camera profiles, the user preferences, and the location information. The life-logging system arranges for the image of the user captured by the camera to be delivered to a client device.

Abstract: Software that uses personalized information pertaining to a user to determine how familiar (or “novel” or “surprising”) a new artifact will be to the user, by performing the following steps: (i) receiving a first dataset pertaining to a first user; (ii) building, utilizing the first dataset, an ontology of artifacts known to the first user, where the ontology includes a domain of food and a plurality of artifacts that include food recipes, and where the artifacts have corresponding characteristics that include food ingredients; (iii) calculating a prior probability distribution for each artifact of the ontology using a probabilistic familiarity algorithm; and (iv) calculating a probabilistic familiarity value for the first artifact with respect to the first user by adding the first artifact to the set of artifacts and calculating the first artifact's prior probability distribution using the probabilistic familiarity algorithm.

Abstract: A method includes activating a first object detector and a second object detector. The first object detector is operable to detect a first type of object in a set of image frames, and the second object detector is operable to detect a second type of object in the set of image frames. The method also includes activating a first set of attribute classifiers and a second set of attribute classifiers. The method also includes generating first statistics for the first object detector and second statistics for the second object detector. The method also includes modifying activation of at least the second set of attribute classifiers based on a comparison of the first statistics and the second statistics.

Abstract: A method includes receiving, by a first device of a transportation provider, a device ID of a particular device of a user and purchase information regarding a purchase, by the user, of one or more goods or services. The method includes sending, by the first device, the device ID of the particular user device to a central server. The method includes receiving, by the first device from the central server, information regarding the particular user device. The method includes determining, by the first device, a selected transportation vehicle based on the purchase information and the information regarding the particular user device. The method includes sending, by the first device, a vehicle ID of the selected transportation vehicle to the central server. The method includes providing a transportation service to the user using the particular user device and the selected transportation vehicle.