Abstract: Disclosed herein are method, system, and computer program product embodiments for filtering website records based on user gestures. In an embodiment, a method can include presenting, via a user device, at least one of a plurality of search filters or a plurality of website records. Further, the method can include receiving, via a touch screen interface of the user device, a user gesture comprising a graphical representation of a search filter input, the user gesture being provided over at least one of a search filter of the plurality of search filters or a website record of the plurality of website records. Additionally, the method can include determining the search filter input from the user gesture, filtering the plurality of web site records based on the search filter input, and presenting, via the user device, a filtered plurality of website records.

Abstract: According to certain aspects of the disclosure, a computer-implemented method may be used for providing a vehicle recommendation based on user gestures. The method may include displaying an image of a vehicle to a user and receiving at least one gesture from the user performed on the image of the vehicle. Additionally, the method may include assigning a value to the at least one gesture from the user and determining a feature of the vehicle based on the at least one gesture from the user. Additionally, the method may include receiving gesture information related to the at least one gesture and determining a vehicle preference of the user based on the value, the feature of the vehicle, and the gesture information. Additionally, the method may include identifying an available vehicle based on the vehicle preference of the user and displaying the available vehicle to the user.

Abstract: Disclosed herein are various embodiments for a vehicle listing generation and optimization system. An embodiment operates by receiving a request to generate a vehicle listing to sell a vehicle on a website. A plurality of vehicle listings similar to the vehicle to be sold are determined, the plurality of vehicle listings including a plurality of features providing information about a respective vehicle featured in the vehicle listing and a performance metric indicating an effectiveness of a respective listing. A first cluster of listings from the plurality of vehicle listings similar to the vehicle are identified based on based on performing artificial intelligence clustering with respect to the metric. Common features amongst a subset of the first cluster of listings are identified. A user interface of a sales template for selling the vehicle associated with the request via the website is generated, wherein the sales template includes the common identified features.

Abstract: A computer-implemented method for providing product recommendations to a user may include receiving audio data from a user device. The audio data may include human speech from a user associated with the user device. The method may further include: performing a speech-to-text process on the audio data to determine text; segmenting the text into discrete conceptual units; identifying keywords that correspond words in the text; associating keywords with the conceptual units having the corresponding words; performing a first analysis process on the conceptual units to determine a first score; performing a second analysis process portions of the human speech correlated with the conceptual units to determine a second score; determining a keyword score for each keyword based on the first and second scores of the conceptual units; determining a product recommendation based on the keywords associated with conceptual units and the corresponding keyword scores; and causing the user device to output the recommendation.

Abstract: Disclosed herein are system, method, and computer program product embodiments for associating a gesture to a website action. In an embodiment, an application receives a user instruction to associate a website action with a user gesture such that the website action occurs upon receipt of the user gesture and the user gesture relates to user input on a user device's display. Thereafter, based on the user instruction, the application creates and sends an interaction request to link the user gesture to the website action. The application then receives an acceptance message from the first website that indicates that the user gesture has been successfully linked to the website action.

Abstract: According to certain aspects of the disclosure, a computer-implemented method may be used for providing a vehicle recommendation based on user gestures. The method may include displaying at least one image of a vehicle to a user and receiving at least one gesture from the user performed on the at least one image of the vehicle. Additionally, the method may include assigning a value to the at least one gesture from the user and determining a feature of the vehicle based on the at least one gesture from the user. Additionally, the method may include receiving gesture information related to the at least one gesture and determining a vehicle preference of the user based on the value, the feature of the vehicle, and the gesture information. Additionally, the method may include identifying at least one available vehicle based on the vehicle preference of the user and displaying the at least one available vehicle to the user.

Abstract: Systems and methods automating the process of application code vulnerability remediation. Implementations include building a repository of code revisions as software is checked for security vulnerabilities using or more software analysis tools. In certain implementations, historical code revisions are cataloged and stored in the repository. The revisions may be tokenized and utilized to detect and automatically remediate similar issues when new software packages are submitted to the system.

Abstract: A device obtains image data associated with a document. Using a first machine learning model, the device determines, for the document, a first classification of one of a plurality of document types and a first confidence score associated with the first classification, and a second classification of one of the plurality of document types and a second confidence score associated with the second classification based on the image data. The device determines a difference between the first confidence score and the second confidence score, compares the difference and a threshold value, and accept the first classification of the document when the difference satisfies the threshold value.

Abstract: Disclosed herein are various embodiments for a vehicle listing generation and optimization system. An embodiment operates by receiving a request to generate a vehicle listing to sell a vehicle on a website. A plurality of vehicle listings similar to the vehicle associated with the request are determined, the plurality of vehicle listings including a plurality of features providing information about a respective vehicle featured in the vehicle listing and a sales time metric specifying a time it took to sell the respective vehicle featured in a respective vehicle listing. Clustering is performed on the set of vehicle listings based on the sales time metrics, and a first cluster is selected. It is identified which of the plurality of features are common amongst at least a subset of the vehicle listings of the selected cluster. A user interface of a sales template for the vehicle associated with the request is generated.

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: In some implementations, a system may receive driving data indicating, for each of a plurality of drivers, driving behavior measured during vehicle operation and importance values corresponding to driving categories associated with the driving behavior. The system may determine driver clusters. The system may receive vehicle data indicating, for each of a plurality of vehicles, performance values corresponding to the driving categories. The system may generate a data structure indicating a degree of association between a vehicle and each driver cluster based on the driving behavior, importance values, and performance values. The system may receive, for a user, driver preference data including data measured during vehicle operation and an importance value for each driving category. The system may determine a driver cluster to which the user belongs based on the driver preference data. The system may determine compatible vehicles based on the driver cluster and the data structure.

Abstract: Systems and methods automating the process of application code vulnerability remediation. Implementations include building a repository of code revisions as software is checked for security vulnerabilities using or more software analysis tools. In certain implementations, historical code revisions are cataloged and stored in the repository. The revisions may be tokenized and utilized to detect and automatically remediate similar issues when new software packages are submitted to the system.

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: Systems and methods for asset interchange are disclosed. In one embodiment, a method includes receiving an indication that a user wants to exchange a first product, determining a plurality of second products different from the first product, identifying a plurality of second users that own at least one of the plurality of second products, generating a bipartite graph representing a plurality of different connections between the user and the plurality of second users, wherein each connection of the plurality of different connections represents an interchange of the first product with one or more of the plurality of second products, generating an interchange recommendation from the bipartite graph, transmitting the interchange recommendation to a first computing device and a second computing device, receiving an interchange approval message from the first computing device and the second computing device, generating interchange instructions, and transmitting the generated interchange instructions.

Abstract: Disclosed herein are system, method, and computer program product embodiments for detecting a potential damage caused to a vehicle when the vehicle is placed on a transporter. The method includes obtaining a first image and a second image taken at different time instances. The first image and the second image are generated by one or more cameras placed around a vehicle on a transporter, and cover a same portion of a body of the vehicle. The method further includes detecting a change between a portion of the first image corresponding to the portion of the body of the vehicle and a portion of the second image corresponding to the portion of the body of the vehicle indicative of a collision. Moreover, the method includes flagging a potential damage to the portion of the body of the vehicle based on the detected change between the first image and the second image.

Abstract: Aspects described provide systems and methods that relate generally to image analysis and, more specifically, overlaying images onto a three-dimensional model of a vehicle. The systems and methods include a vehicle application that receives vehicle information via a user interface. The vehicle application receives a plurality of images that comprise images of one or more internal components of the vehicle and images of one or more external components of the vehicle. The vehicle application utilizes a machine learning model to classify actual current images and attach, overlay, and wrap the actual current images to a three-dimensional model of the vehicle. The machine learning model and vehicle application meshes the actual current images around the three-dimensional model of the vehicle to create a three-dimensional view of the vehicle. The vehicle application further displays via the user interface the three-dimensional view of the vehicle.

Abstract: Disclosed are methods, systems, and non-transitory computer-readable medium for estimating a value of a future vehicle. For instance, the method may include receiving a request for a target vehicle value estimate, obtaining an optical scan of a vehicle, generating a vehicle reference, the mileage of the vehicle, and the feature set of the vehicle, comparing the optical scan to the vehicle reference to identify one or more differences between the surfaces of the vehicle and corresponding surfaces of the vehicle reference that are indicative of damage or wear, and evaluating a relative condition of the vehicle based on those differences. The method may further include retrieving a target vehicle reference, generating a projection of a future condition of the target vehicle based on the relative condition of the vehicle, retrieving third-party vehicle records relevant to the target vehicle, and determining an estimated future value of the target vehicle.

Abstract: An embodiment of a customer callback system 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: A system, method, and computer-readable medium for associating a person’s gestures with specific features of objects is disclosed. Using one or more image capture devices, a person’s gestures and the location of that person in an environment is determined. Using determined distances between the person and objects in the environment and scales associated with features of those objects, the list of specific features in the person’s field-of-view may be determined. Further, a facial expression of the person may be scored and that score associated with one or more specific features.

Abstract: Aspects described provide systems and methods that relate generally to image analysis and, more specifically, identifying individual components and elements in an image. The systems and methods include a valuation application executing one or more application program interfaces (APIs) communicating with one or more websites via a network, where the user is prompted to enter information and/or take pictures or videos of their vehicle that they would like to sell. The valuation application utilizes a machine learning model to identify and value the various vehicle components within the images and videos. Based on the machine learning model, the valuation application identifies each component according to the images and videos and performs a search to determine the value of the components identified. The valuation application tabulates and summarizes the vehicle component resale values and resell information for the user to view.