Abstract: Techniques described herein can monitor various data metrics. The auto-insight techniques can further detect and rank data segments that contributed to, or counteracted, shifts in data and detect when such shifts occurred. Thus, the techniques described herein can detect and identify root causes in shifts in different metrics. The techniques include pruning and ranking causes to identify the root causes and identify non-relevant factors, as well.

Abstract: Techniques described herein can monitor various data metrics. The auto-insight techniques can further detect and rank data segments that contributed to, or counteracted, shifts in data and detect when such shifts occurred. Thus, the techniques described herein can detect and identify root causes in shifts in different metrics. The techniques include pruning and ranking causes to identify the root causes and identify non-relevant factors, as well.

Abstract: Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

Abstract: Techniques described herein can monitor various data metrics. The auto-insight techniques can further detect and rank data segments that contributed to, or counteracted, shifts in data and detect when such shifts occurred. Thus, the techniques described herein can detect and identify root causes in shifts in different metrics. The techniques include pruning and ranking causes to identify the root causes and identify non-relevant factors, as well.

Abstract: Techniques described herein can monitor various data metrics. The auto-insight techniques can further detect and rank data segments that contributed to, or counteracted, shifts in data and detect when such shifts occurred. Thus, the techniques described herein can detect and identify root causes in shifts in different metrics. The techniques include pruning and ranking causes to identify the root causes and identify non-relevant factors, as well.

Abstract: Techniques described herein can monitor various data metrics. The auto-insight techniques can further detect and rank data segments that contributed to, or counteracted, shifts in data and detect when such shifts occurred. Thus, the techniques described herein can detect and identify root causes in shifts in different metrics. The techniques include pruning and ranking causes to identify the root causes and identify non-relevant factors, as well.

Abstract: Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

Abstract: Embodiments herein relate to an autonomous vehicle or self-driving vehicle. The system can determine a collision avoidance path by: 1) predicting the behavior/trajectory of other moving objects (and identifying stationary objects); 2) given the driving trajectory (issued by autonomous driving system) or predicted driving trajectory (human), establishing the probability for a collision that can be calculated between the vehicle and one or more objects; and 3) finding a path to minimize the collision probability.

Abstract: Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.

Abstract: Embodiments herein relate to an autonomous vehicle or self-driving vehicle. The system can determine a collision avoidance path by: 1) predicting the behavior/trajectory of other moving objects (and identifying stationary objects); 2) given the driving trajectory (issued by autonomous driving system) or predicted driving trajectory (human), establishing the probability for a collision that can be calculated between the vehicle and one or more objects; and 3) finding a path to minimize the collision probability.

Abstract: A network crawler crawls one or more media sites to extract a plurality of titles for information contained in the one or more media sites. For example, the network crawler may extract the titles on the one or more media sites by identifying different computer formats and converting the titles in the different computer formats into a common computer format for comparison. User profiles which, includes user's interest are stored in a user profile interest database. A novel personalized news recommendation engine recommends news similar to the interest specified in a user profile, where maximum weighted matching is applied to score the similarity of news against user interest in the word2vec space.

Abstract: Systems of an electrical vehicle and the operations thereof are provided. A method for controlling access to a vehicle includes a processor of a vehicle control system determining a signal strength for sensors of a vehicle. The processor determines a location of a user device based on the determined signal strength for the sensors. The processor enables a gesture recognition system based on the determination of the location of the user device. The processor receives data from the user device, determines a type of gesture associated with the received data from the user device, and activates one or more functions of the vehicle based on the determined type of gesture.

Abstract: Embodiments can provide an intelligent vehicle that determines that the vehicle interior comprises multiple occupants; identifies the occupants; based on the driving behavior of the vehicle, creates a composite occupant profile associated with the group of plural occupants, the composite occupant profile comprising the identities of the plural occupants and group preferences for various vendor products or services; and, based on the composite occupant profile and received inputs from a user interface, an automatic vehicle location system, and a plurality of sensors in the vehicle, performs one or more actions, such as: (a) proposing one or more vendor products or services for the group of occupants; (b) publishing the vendor products or services selected by the group of occupants, via a social network, to associated or selected associates of the occupants in the group; and (c) presenting advertisement information from a vendor server associated with the proposed or selected vendor products or services to one

Abstract: Embodiments herein relate to an autonomous vehicle or self-driving vehicle. The level of comfort with autonomous driving offered to the user and the parameters of operation of the autonomous vehicle might increase or decrease a driver's comfort (anxiety) with the vehicle. Sensors in the vehicle can detect a user's driving style, comfort level and may propose an autonomy level to the user and/or parameters of operation.

Abstract: Systems of an autonomous vehicle and the operations thereof are provided. The vehicle can predict a user's trip using his or her history of past trips, the relevant context, and the current environmental conditions. The navigation system of the vehicle can use historical GPS data, defined by the sequence of position measurements, of a given vehicle to determine frequently visited locations. Then, the navigation system may augment the learned knowledge of frequently visited locations and routes with the relevant context and environmental conditions to make recommendations on the locations the user is most likely to visit and the route most likely to drive on. More specifically, the navigation system can automatically cluster historical trips by similarity (e.g., trips with similar contexts and/or environmental conditions), while identifying, mitigating, and/or eliminating the potential for statistical outliers (trips taken by a driver that are infrequent and thus less useful for predicting future trips).

Abstract: An automated system for controlling a vehicle gathers a set of sensor information for a series of driving actions that comprises a driving path of an individual driver. A context is determined that is related to the set of sensor information for the series of driving actions that comprise the driving path of the individual driver. For example, the context may be a weather condition or when the driver merges into traffic. A personalization score is determined for the series of driving actions for the individual driver based on the context. A personalization score is determined for one or more other driving paths and a driving path with the highest personalization score is identified. The driving path with the highest personalization score is then chosen for automated driving.

Abstract: A network crawler crawls one or more media sites to extract a plurality of titles for information contained in the one or more media sites. For example, the network crawler may extract the titles on the one or more media sites by identifying different computer formats and converting the titles in the different computer formats into a common computer format for comparison. User profiles which, includes user's interest are stored in a user profile interest database. A novel personalized news recommendation engine recommends news similar to the interest specified in a user profile, where maximum weighted matching is applied to score the similarity of news against user interest in the word2vec space.

Abstract: Systems of an electrical vehicle and the operations thereof are provided. Electric vehicles may be routed from a start location to a destination through a network of charging stations explicitly considering time-varying uncertainty in both charging times, queueing times, and range. The routing objective may be a function of trip duration, electric vehicle state of charge at any time or location along the trip, uncertainty in the vehicle state of charge, the estimated trip duration, etc. Uncertainty in a distribution may be computed using an information-theoretic metric such as entropy. Waiting times may be estimated at an electric vehicle charging station given observed data for that station. An estimated waiting time at a charging station can be communicated directly to the owner of an electric vehicle owner or used to design a robust system for routing through charging stations.

Abstract: An automated system for controlling a vehicle gathers a set of sensor information for a series of driving actions that comprises a driving path of an individual driver. A context is determined that is related to the set of sensor information for the series of driving actions that comprise the driving path of the individual driver. For example, the context may be a weather condition or when the driver merges into traffic. A personalization score is determined for the series of driving actions for the individual driver based on the context. A personalization score is determined for one or more other driving paths and a driving path with the highest personalization score is identified. The driving path with the highest personalization score is then chosen for automated driving.

Abstract: Embodiments herein relate to an autonomous vehicle or self-driving vehicle. The level of comfort with autonomous driving offered to the user and the parameters of operation of the autonomous vehicle might increase or decrease a driver's comfort (anxiety) with the vehicle. Sensors in the vehicle can detect a user's driving style, comfort level and may propose an autonomy level to the user and/or parameters of operation.