Abstract: Described herein are examples of a system that processes information describing movement of a vehicle at a time related to a potential collision to reliably determine whether a collision occurred and/or one or more characteristics of the collision. In response to obtaining information regarding a potential collision, data describing movement of the vehicle before and/or after a time associated with the potential collision is analyzed to determine whether the collision occurred and/or to determine one or more collision characteristic(s). The analysis may be carried out at least in part using a trained classifier that classifies the vehicle movement data into one or more classes, where at least some the classes are associated with whether a collision occurred and/or one or more characteristics of a collision. If a collision is determined to be likely, one or more actions may be triggered based on the characteristic(s) of the collision.

Abstract: Generating questions by receiving user utterance data, determining an intent confidence vector for the user utterance data, predicting, by a trained next user-intent prediction model, a next user-intent confidence vector using the intent confidence vector, and generating a next question using the next user-intent confidence vector.

Abstract: Systems and methods for grouping telematics vehicle data in one or more zones are provided herein. Systems and methods for generating zones and providing vehicle information associated with the one or more zones are also provided. Systems and methods for parallelizing zone generation and addressing zones disposed adjacent a boundary of a geographical are also provided.

Abstract: An electro-hydraulic flow control system for controlling the movement of a cutting implement of a turf mower. The flow control system comprises a hydraulic system for raising and lowering the cutting implement. The hydraulic system comprises a hydraulic fluid, a hydraulic actuator, and a hydraulic pump. The control system additionally comprises an electromechanical fluid flow control system for controlling a flow of the hydraulic fluid through the hydraulic system. The electromechanical fluid control system comprises a routing valve, a float valve, a weight transfer valve, a weight transfer pressure adjustment (WTPA) valve, and a control module for control operation of the routing valve, the float valve, the weight transfer valve, and the WTPA valve to control operation of the actuator and thereby control movement of the cutting implement.

Abstract: Removing disfluencies from an audio stream is disclosed, including: receiving an audio stream comprising payload segments and disfluency segments; determining windows of audio in the audio stream; identifying the disfluency segments in the audio stream using the windows of audio; and modifying the audio stream by removing at least a portion of the disfluency segments.

Abstract: Described herein are examples of a system that processes information describing movement of a vehicle at a time related to a potential collision to reliably determine whether a collision occurred and/or one or more characteristics of the collision. In response to obtaining information regarding a potential collision, data describing movement of the vehicle before and/or after a time associated with the potential collision is analyzed to determine whether the collision occurred and/or to determine one or more collision characteristic(s). The analysis may be carried out at least in part using a trained classifier that classifies the vehicle movement data into one or more classes, where at least some the classes are associated with whether a collision occurred and/or one or more characteristics of a collision. If a collision is determined to be likely, one or more actions may be triggered based on the characteristic(s) of the collision.

Abstract: A method, system, and computer program product for routing queries to answer resources based on component parts and intents of a received query is provided. The method receives a query from a user. The query is analyzed to identify a set of entities associated with the query and generate an utterance representing the query. The method generates an intent classification for the utterance and a vector for the query. The vector is generated based on the set of entities, the utterance, and the intent classification. The method determines an answer resource for the query based on the vector and the intent classification of the query. In response to determining the answer resource, the method provides an answer interface based on the query, the vector, and the intent classification. The answer interface dynamically provides a response to the query.

Abstract: A computer-implemented method, a computer system, and a computer program product for automatically generated conversation output is provided. The present invention may include training an answer-intent classifier to associate an intent expressed in an example question with an example answer that is responsive to the example question. The present invention may further include classifying, using the trained answer-intent classifier, a content transmitted to the trained answer-intent classifier with the intent expressed in the example question in response to determining, using the trained answer-intent classifier, that the content includes relevant information for generating the example answer that is responsive to the example question.

Abstract: Systems and methods for associating vehicle trip data with a base map are provided herein. Systems and methods for providing vehicle trip data showing the greatest usage of routes between an origin and destination are also provided. Systems and methods for predicting a speed limit of a road based on vehicle trip data are also provided. Systems and methods for providing vehicle trip data showing popular stops between an origin and a destination are also provided. Systems and methods for providing contiguous region identification based on vehicle trip data are also provided.

Abstract: An adversarial reinforcement learning system is used to simulate a spatial environment. The system includes a simulation engine configured to simulate a spatial environment and various objects therein. The system further includes a first model configured to control objects in the simulation and a second model configured to control objects in the simulation. The first model generates a threat-mitigation input to control one or more objects in the simulation, and the second model generates a threat input to control one or more objects in the simulation. The system then executes a first portion of the simulation based at least in part of the threat mitigation input and the threat input.

Abstract: A method, computer system, and a computer program product for automatically generated question suggestions is provided. The present invention may include generating an intent-entity sequence representative of a current chat conversation with a user. The present invention may also include predicting, using a trained intent-entity prediction model, a next intent-entity sequence based on the generated intent-entity sequence representative of the current chat conversation. The present invention may further include converting the predicted next intent-entity sequence into at least one likely question suggestion to return back to the user.

Abstract: Generating questions by receiving user utterance data, determining an intent confidence vector for the user utterance data, predicting, by a trained next user-intent prediction model, a next user-intent confidence vector using the intent confidence vector, and generating a next question using the next user-intent confidence vector.

Abstract: Described herein are methods of estimating a chance of precipitation in an area that include identifying one or more vehicles in the area and determining the likelihood of precipitation using telematics data for the one or more vehicles in the area. Also described herein are methods that include receiving telematics data from a plurality of vehicles, wherein the telematics data is associated with a location, analyzing the telematics data to identify vehicle events associated with one or more segments of road, analyzing weather information associated with the one or more segments of road, and determining a correlation between the weather information and the vehicle events.

Abstract: Described herein are methods of estimating a chance of precipitation in an area that include identifying one or more vehicles in the area and determining the likelihood of precipitation using telematics data for the one or more vehicles in the area. Also described herein are methods that include receiving telematics data from a plurality of vehicles, wherein the telematics data is associated with a location, analyzing the telematics data to identify vehicle events associated with one or more segments of road, analyzing weather information associated with the one or more segments of road, and determining a correlation between the weather information and the vehicle events.

Abstract: Described herein are methods of estimating a chance of precipitation in an area that include identifying one or more vehicles in the area and determining the likelihood of precipitation using telematics data for the one or more vehicles in the area. Also described herein are methods that include receiving telematics data from a plurality of vehicles, wherein the telematics data is associated with a location, analyzing the telematics data to identify vehicle events associated with one or more segments of road, analyzing weather information associated with the one or more segments of road, and determining a correlation between the weather information and the vehicle events.

Abstract: Described herein are methods of estimating a chance of precipitation in an area that include identifying one or more vehicles in the area and determining the likelihood of precipitation using telematics data for the one or more vehicles in the area. Also described herein are methods that include receiving telematics data from a plurality of vehicles, wherein the telematics data is associated with a location, analyzing the telematics data to identify vehicle events associated with one or more segments of road, analyzing weather information associated with the one or more segments of road, and determining a correlation between the weather information and the vehicle events.

Abstract: In an approach for identifying when transferring a real-time conversation on a chatbot application to a customer support agent would be more valuable than outputting suggested queries, a processor classifies a query inputted into a real-time conversation as an intention. A processor predicts a set of next intentions of the user. A processor filters out one or more intentions from the set of next intentions of the user that do not further the real-time conversation. A processor generates a set of suggested queries the user can ask to further the real-time conversation from the subset of next intentions. A processor builds a suggestion evaluation contextual bandit model that determines whether the real-time conversation will be resolved successfully if transferred to a customer support agent. A processor trains the suggestion evaluation contextual bandit model against a set of annotated historical interactions. A processor outputs a response recommendation.

Abstract: Disclosed are systems and methods for determining a geographical area occupied by an intersection.

Abstract: Disclosed are systems and methods relating to determining geographic locations of vehicle ways which are employed by vehicles for movement and/or parking. A classifier may be defined for identifying portions of the vehicle ways via machine learning techniques and processing of historical telematic data.

Abstract: An adversarial reinforcement learning system is used to simulate a security checkpoint. The system includes a simulation engine configured to simulate a security checkpoint and various threat objects and threat-mitigation objects therein. The system further includes an attack model configured to control threat objects in the simulation and a defense model configured to control threat-mitigation objects in the simulation. A first portion of the simulation is executed by the simulation engine in order to generate an outcome of the first portion of the simulation. The defense model then generates a threat-mitigation input to control threat-mitigation objects in a subsequent portion of the simulation, and the attack model then generates a threat input to control threat objects in the subsequent portion of the simulation, wherein the inputs are based in part on the outcome of the first portion of the simulation.