Abstract: Systems, methods, and computer-readable storage media for generating a flight path for aerial drones around parked vehicles, where the flight path navigates an aerial drone to specific locations associated with predetermined views of the vehicle. A remotely located user can select from a list of predetermined views where the drone should travel, and the computer system can direct the drone to a location associated with the selected view, align the camera on the drone to capture the selected view, and relay live video of the selected view of the parked car to the user.

Abstract: A set of queries from an application executing on a client computing device is obtained. A first database based on the set of queries is searched to select a set of event types. A set of predicted parameters associated with the set of event types is sent to the application. The application includes instructions to obtain a first parameter and the set of predicted parameters via a user interface of the application and generate a message comprising the first parameter and an indicator identifying the set of predicted parameters. The first parameter and the indicator are obtained via the second message. A combined query including the first parameter and the set of predicted parameters is generated in response to obtaining the indicator. A vehicle record from the vehicle database is obtained based on the combined query. Values of the vehicle record are sent to the client computing device.

Abstract: Aspects described herein may allow for generating a filter list to facilitate users to refine their online search. Data items displayed on a web page may be determined based on the user's input data, for example, based on a selection command selecting the data items. Each data item corresponds to a feature of a product. Filters corresponding to the data items may be determined and the weight of each filter may be updated. A filter list may be generated and displayed to facilitate the user to refine his search for a class of products. The filters on the filter list may be automatically ordered based on the weight of each filter. In this way, a user may be able to find filters that are associated with features that he cares about the most and therefore use the filter list to obtain more satisfying results.

Abstract: An inquiry analysis system and method are disclosed. An inquiry analysis system includes a computer configured to receive an electronic communication from a user, the electronic communication comprising an inquiry associated with an article of interest. The inquiry analysis system determines one or more measures including a first result of a first trained model based on one or more content elements of the inquiry, a second result of a second trained model based on one or more sentiment elements of the inquiry, and a valuation divergence model result based on a comparison of the inquiry with a reference value associated with the article of interest. The inquiry analysis system calculates and outputs a composite interest prediction which predicts a level of interest of the user associated with the respective article of interest.

Abstract: An augmented reality system including processors and storage devices storing instructions. The instructions may configure the processors to perform operations including determining a location of a mobile device, identifying a facility based on the location, requesting mapping data from a facility server, the mapping data comprising a plurality of vehicles, vehicle location data, and landmarks, identifying one location attribute in a video feed captured by an augmented reality viewer displayed in the mobile device, and determining whether the one location attribute matches the plurality of vehicles or the landmarks. The operations may also include identifying qualified vehicles from the vehicles based on qualification criteria, determining whether the qualified vehicles is in a field of view of the augmented reality viewer based on object attributes and the vehicle location data, and generating a modified video feed by providing an indication associated with qualified vehicles in the field of view.

Abstract: Methods, media and systems are provided for enhancing a web browsing session. Methods and media include retrieving a user profile containing information related to a potential vehicle buyer or a vehicle profile containing information related to a vehicle of interest. Historical use data of a web browser associated with the corresponding user profile is retrieved. Enhancing the web browsing session further includes analyzing an input received from a current web browser session associated with the user profile or vehicle profile and determining a vehicle characteristic related to the analyzed input. An automated phrase corresponding to the vehicle characteristic is selected to elicit further user interaction during the current web browser session. The selected automated phrase is based on the determined vehicle characteristic. Systems include a profile database for storing user/vehicle profiles and a memory storing a set of computer-executable instructions to enhance a web browsing session.

Abstract: A system and method for queue management is disclosed. The system and method includes at least: (a) monitoring, by one or more computing devices, a network node queue to determine a value indicating how much data is processed by the network node over a period of time; (b) determining, by the one or more computing devices, whether the value is below a threshold value, wherein the value being below the threshold value indicates a performance degradation of the network node; (c) based on determining the value is below the threshold value, removing, by the one or more computing devices, a remaining data from the network node queue; and (d) transmitting, by the one or more computing devices, the remaining data removed in (c) to a coordinator module for redistribution to one or more other network nodes to process the remaining data.

Abstract: The disclosure describes a system and methods for implementing a recommendation engine. The recommendation engine can at least receive a travel history log, wherein the travel history log includes a route traversed by a customer; receive a route information from a database for the route, where the route information includes an accident history for the route; generate a route traverse percentage based on the travel history log; generate a route categorization score based on the accident history for the route and the route traverse percentage; and generate a vehicle recommendation based on the route categorization score.

Abstract: Systems, methods, and computer readable media for vehicular search recommendations using machine learning. A computing model may receive a query for a vehicular recommendation. The model may be trained based on historical queries, webpages visited, and attributes of vehicles. The model may generate a decision tree comprising a plurality of paths for processing the query, the plurality of paths comprising a subset of a plurality of available paths for processing the query, each path associated with a plurality of search phases. The model may select, based on the decision tree, a first path of the plurality of paths for processing the query. The model may select, based on the first path, a first search phase of the plurality of search phases as corresponding to the query. The model may then return a search result corresponding to the first search phase as responsive to the query.

Abstract: In certain embodiments, access to a plurality of sites associated with a plurality of users may be obtained. The plurality of sites may comprise categories of the plurality of users and interactions among the plurality of users. Based on the plurality of sites, a plurality of interaction datasets and a plurality of timing datasets may be generated. The plurality of interaction datasets and the plurality of timing datasets may be provided as inputs to a machine learning model and the machine learning model may be configured based on the inputs. Subsequent to the configuration, an interaction dataset and a timing dataset associated with a user may be provided to the machine learning model. A predicted length of time for the user may be obtained via the machine learning model and one or more settings of a program may be configured to the user based on the predicted length of time.

Abstract: In some implementations, a system may receive an indication that a user device is near a proximate vehicle. The system may obtain a user profile associated with the user device that indicates a vehicle attribute category as being of interest to a user. The system may obtain first audio content based on the proximate vehicle and the vehicle attribute category that describes a proximate vehicle attribute corresponding to the vehicle attribute category. The system may identify, based on the vehicle attribute category, a target vehicle located near the proximate vehicle that compares more favorably to a user preference compared to the proximate vehicle. The system may obtain second audio content based on the target vehicle and the user preference that describes a comparison between the proximate vehicle attribute and a target vehicle attribute of the target vehicle. The system may output the first audio content and the second audio content.

Abstract: Disclosed herein are various embodiments for a customer callback system. An embodiment operates by determining a call action indicating a customer to whom a representative is to speak. An identifier associated with the customer is determined. A plurality of computing activities corresponding to interactions between the computing device and one or more websites provided to the computing device over a defined period of time are retrieved. A pattern associated with when the plurality of computing activities corresponding to the interactions between the computing device and the one or more websites were performed is identified. The overlapping time of day is provided to the representative during which to perform the call action.

Abstract: Disclosed are systems and methods for generating and displaying models for routes using a machine learning engine. The method may include: receiving a plurality of route data sets, each associated with a route; determining a route score for each route; receiving a plurality of driver data sets, each associated with a driver; determining a driver score for each driver; generating a model for each driver based on a respective driver score and a respective route score; grouping the route data sets into clusters; training a neural network to associate each cluster with one or more sequential patterns found within the cluster; receiving a first driver data set and a first route data set; generating a first route score and a first driver score; generating, a first model based on the first route score and the first driver score.

Abstract: Embodiments disclosed are directed to a system that performs steps to monitor a geographic area to detect a triggering event. The triggering event can inform the system that there is a data transmission problem scenario within the geographic area. The triggering event can cause a distributor node to distribute data to one or more devices within the geographic area. The system can select the distributor node by determining whether a projected travel path of a node will overlap with the geographic area. The system can further determine whether the distributor node has entered the geographic area, and activate the distributor node to distribute data to the one or more devices within the geographic area.

Abstract: A computer-implemented method for providing a vehicle recommendation may include obtaining characteristic data of a user-defined vehicle based on one or more interactive activities of a user with a first three-dimensional model of a model vehicle; generating a second three-dimensional model of the user-defined vehicle based on the first three-dimensional model and the characteristic data; obtaining one or more images of the second three-dimensional model; generating a selection of one or more pre-stored vehicles based on a comparison between the one or more images of the second three-dimensional model and pre-stored image data of the one or more pre-stored vehicles other than the user-defined vehicle; obtaining user feedback data based on the selection of the one or more pre-stored vehicles; generating the vehicle recommendation for the user based on the user feedback data; and transmitting, to a device associated with the user, a notification indicative of the vehicle recommendation.

Abstract: A system and method for queue management is disclosed. The system and method includes at least: (a) monitoring, by one or more computing devices, a network node queue to determine a value indicating how much data is processed by the network node over a period of time; (b) determining, by the one or more computing devices, whether the value is below a threshold value, wherein the value being below the threshold value indicates a performance degradation of the network node; (c) based on determining the value is below the threshold value, removing, by the one or more computing devices, a remaining data from the network node queue; and (d) transmitting, by the one or more computing devices, the remaining data removed in (c) to a coordinator module for redistribution to one or more other network nodes to process the remaining data.

Abstract: An image processing system may receive a set of images and may detect a plurality of features of an object included in the set of images. The image processing system may determine metadata associated with the set of images that indicates a relative importance of a first feature, of the plurality of features, as compared to a second feature, of the plurality of features. The image processing system may select, based on the metadata, a set of features of the plurality of features and may perform a search based on the set of features to identify a set of objects having a same object category as the object and that have a visual characteristic that shares a threshold degree of similarity with a corresponding visual characteristic of at least one feature included in the set of features. The image processing system may output results that identify the set of objects.

Abstract: The disclosure describes a system and methods for implementing a recommendation engine. The recommendation engine can at least receive a travel history log, wherein the travel history log includes a route traversed by a customer; receive a route information from a database for the route, where the route information includes an accident history for the route; generate a route traverse percentage based on the travel history log; generate a route categorization score based on the accident history for the route and the route traverse percentage; and generate a vehicle recommendation based on the route categorization score.

Abstract: An augmented reality system including processors and storage devices storing instructions. The instructions may configure the processors to perform operations including determining a location of a mobile device, identifying a facility based on the location, requesting mapping data from a facility server, the mapping data comprising a plurality of vehicles, vehicle location data, and landmarks, identifying one location attribute in a video feed captured by an augmented reality viewer displayed in the mobile device, and determining whether the one location attribute matches the plurality of vehicles or the landmarks. The operations may also include identifying qualified vehicles from the vehicles based on qualification criteria, determining whether the qualified vehicles is in a field of view of the augmented reality viewer based on object attributes and the vehicle location data, and generating a modified video feed by providing an indication associated with qualified vehicles in the field of view.

Abstract: A computer-implemented method that includes receiving a request for a target vehicle including input data associated with an operator, a geographic location, and the target vehicle. The method includes determining a depreciation rate based on third-party transaction data retrieved from databases in accordance with the input data associated with the target vehicle, and a decommission rate based on third-party ownership data retrieved from databases in accordance with the input data associated with the target vehicle. The method includes determining a deterioration rate based on local environmental data retrieved from databases in accordance with the input data associated with the geographic location, and generating a regression model configured to compute an estimated value of the target vehicle during a lifetime of the target vehicle using the input data, depreciation rate, decommission rate, and deterioration rate. The method includes determining an output in response to the request for the target vehicle.