Abstract: A computer-implemented method for providing personalized purchasing information to a user may include: obtaining first identification data of the user from a first engine; verifying a registration status of the user based on the first identification data; obtaining second identification data of the user from a second engine based on the registration status of the user; comparing the first identification data of the user and the second identification data of the user; initiating a real-time credit monitoring session based on the comparison between the first identification data of the user and the second identification data of the user; generating the personalized purchasing information of the user based on the real-time credit score of the user; and demonstrating the personalized purchasing information on a display of a device associated with the user.

Abstract: A device receives image data of a contractual document that includes an offer including terms of a proposed transaction, converts the image data to text data that identifies text within the contractual document, and receives preferences information for a recipient of the offer. The device identifies key terms within the contractual document by using term identification to analyze the text. The key terms may include a first key term that identifies subject matter of the proposed transaction and other key terms that are part of the offer. The device determines term scores that correspond to likelihoods of the other key terms being favorable to the recipient by using a data model to analyze the key terms and the preferences information. The device, based on the term scores, generates and provides another device with a recommendation to be used in determining whether the accept the offer.

Abstract: A device may determine a price of a product based on first information concerning attributes of the product, and provide the price for display by a user device. The device may generate first hash values based on the first information, where a particular first hash value is associated with a particular attribute, and generate a first bit-string that includes the plurality of first hash values. The device may generate second hash values based on second information concerning the attributes of the product, where a particular second hash value is associated with the particular attribute. The device may generate a second bit-string that includes the second hash values, and determine a change to the particular attribute based on the first bit-string and the second bit-string. The device may determine a new price of the product based on the change, and provide the new price for display by the user device.

Abstract: The present disclosure is directed to techniques to facilitate online commerce by leveraging user activity, specifically search activity for goods/services on an online platform. As described herein, the online platform refers to a turnkey e-commerce solution that enterprises use to manage electronic transactions involving their goods/services. Some techniques are directed to an improved online platform operative to predict a user's intention behind a search query and after a consider number of search queries, to have that search query as a dynamic search filter for the online platform. Other embodiments are described and claimed.

Abstract: A device may determine that a user device, associated with a user, and a first object for comparison are within a threshold proximity of one another. The device may communicate with the user device to obtain a comparison profile, associated with the user, based on determining that the user device and the first object are within the threshold proximity of one another. The device may identify, based on the comparison profile, a set of desired attributes. The device may identify, based on the comparison profile, a set of attribute categories to be used to compare the first object and the set of desired attributes. The device may determine a first set of attributes of the first object for the set of attribute categories. The device may present, for display, information that identifies one or more attributes of the first set of attributes or the set of desired attributes.

Abstract: Various embodiments are generally directed to techniques of overlaying a virtual object on a physical object in augmented reality (AR). A computing device may receive one or more images of the physical object, perform analysis on the images (such as image segmentation) to generate a digital outline, and determine a position and a scale of the physical object based at least in part on the digital outline. The computing device may configure (e.g., rotate, scale) a 3D model of the physical object to match the determined position and scale of the physical object. The computing device may place or overlay a 3D virtual object on the physical object in AR based on a predefined location relation between the 3D virtual object and the 3D model of the physical object, and further, generate a composite view of the placement or overlay.

Abstract: Disclosed are a system and techniques for identity and electronic signature verification that utilizes blockchain technology. An enterprise system enables computing devices to engage the enterprise and prospective users for the purposes of executing a document or a smart contract. Users may obtain a computer application from an enterprise system and may utilize the computer application to retrieve a document or select a smart contract. The identity of all users who execute the document may be verified based on an authentication by a trusted independent system. Information related to the respective signers, the document or smart contract, and the authentication may be stored as transactions in a blockchain. The transactions may be stored in the blockchain under a user's address, a document or smart contract address, or a digital wallet, if available.

Abstract: Computer-implemented methods, computer systems, and computer readable media for determining, sorting, or determining and sorting a set of items. The method includes receiving, via a user device, parameter values from a user and receiving parameter weights. The method further includes determining a sort score for each vehicle of a set of vehicles based on the received parameter values and parameter weights, and sorting the set of vehicles based on the sort score of each vehicle of the set of vehicles.

Abstract: Various embodiments are generally directed to techniques to provide specific vehicle recommendations to generic user requests. Various techniques, methods, systems, and apparatuses include utilizing one or more tags generated by application of a machine learning model to a data source, where the data source may include generic and specific language with respect to one or more automobiles or vehicles, to provide a recommendation for a particular automobile in response to a user request for a suggestion.

Abstract: The present disclosure relates to interactive projection systems. In one implementation, an interactive projection system for a vehicle window may include a film having a plurality of sensors embedded therein, the plurality of sensors configured to detect local pressure disturbance on the film; a projector configured to project a user interface onto the film; and at least one processor. The at least one processor may be configured to perform operations, including receiving a detection of a local pressure disturbance from at least one of the plurality of sensors, based on a location of the detected local pressure disturbance, determining a change in the user interface, and transmitting a command to the projector to modify a projected user interface according to the determined change.

Abstract: A device receives an image including image data of a scale model of a vehicle, and processes the image data, with a model, to identify a make, a model, and a year represented by the scale model. The device determines augmented reality (AR) vehicle information based on the make, the model, and the year represented by the scale model of the vehicle, and provides the AR vehicle information to enable a user device to associate the AR vehicle information with the image of the scale model of the vehicle. The device receives an input associated with the AR vehicle information, and determines updated AR vehicle information based on the input associated with the AR vehicle information. The device provides the updated AR vehicle information to enable the user device to associate the updated augmented reality vehicle information with the image of the scale model of the vehicle.

Abstract: Embodiments disclosed herein provide for a system and method for recalibrating an augmented reality experience in mobile devices using a plurality of physical markers. The system and methods provide for realigning the digital representation to the physical world using known physical locations associated with the physical markers that map directly to the digital representation.

Abstract: A computer-implemented method for providing a vehicle recommendation to a user may include: obtaining one or more vehicle images via a device associated with the user; identifying one or more user-selected images of the one or more vehicle images based on user interaction with the one or more vehicle images performed by the user via a user interface; identifying one or more first-level attributes from the one or more user-selected images; obtaining one or more vehicle identifications from the one or more user-selected images; determining one or more second-level attributes based on the one or more vehicle identifications; determining a value of each of the one or more first-level attributes and the one or more second-level attributes; determining the vehicle recommendation based on the value; and transmitting, to the device associated with the user, a notification indicating the vehicle recommendation.

Abstract: Techniques for providing indirect local geo-positioning using AR markers are disclosed. A first movable AR marker can be located or found by a computing device. A location of the first movable AR marker can be known and shared with the computing device. The location of the first movable AR marker can be based on distance between the first movable AR marker and a fixed AR marker. A distance to the first movable AR marker can be determined. Based on the known location of the first movable AR marker and the distance to the first movable AR marker from the computing device, an estimate of the location of the computing device can be determined without having line-of-sight (LOS) to the fixed AR marker.

Abstract: Systems as described herein may include authorizing the sharing of data and sharing data between a variety of systems. A request to share data may be provided to a first system. The system may create sharing session data on a distributed ledger accessible by a number of systems. Sharing session data may be stored using a transaction stored on a distributed ledger. A second system may obtain the sharing session account and verify the sharing session. On verification of the sharing session, a variety of data may be shared between the systems identified in the sharing session data. The sharing session data may be established between two or more systems. The distributed ledger may be maintained by the systems themselves and/or a distributed network system. In a variety of embodiments, encrypted data may be stored and/or obtained using the distributed ledger.

Abstract: An autonomous vehicle vendor lot may include a plurality of vehicle selection indicators, a visual navigation system, and a control system. The indicators may be distributed in the lot, associated with a respective parking spot in the lot, and operable to generate a visual indication indicative of a selection of a vehicle in the respective parking spot. The navigation system may be operable to generate a visual indication of a route between various locations in the lot. The control system may be operatively connected to the indicators and the navigation system, and configured to: receive a vehicle search query; identify at least one vehicle in the lot corresponding to the query; operate each vehicle selection indicator corresponding to each identified vehicle; identify a respective location in the lot for each identified vehicle; and operate the visual navigation system to generate a visual indication of a route to at least one identified vehicle.

Abstract: A valuation platform may receive, from a user device, video data associated with a vehicle, and may receive a vehicle history report of the vehicle based on a vehicle identification number of the vehicle. The valuation platform may receive, from the user device, feature data associated with the vehicle, and may process the video data, the vehicle history report, and the feature data, with a machine learning model, to determine one or more values for the vehicle. The valuation platform may determine a valuation for the vehicle based on the determined one or more values for the vehicle. The valuation platform may create a vehicle profile for the vehicle based on the video data, the vehicle history report, the feature data, the determined one or more values for the vehicle, and the valuation for the vehicle, and may perform one or more actions based on the vehicle profile.

Abstract: Aspects described herein may allow for auto-locating a user in a parking lot and/or automatically directing a user to recommended inventory. For example, a customer may capture an image of a vehicle, or a marker associated with a vehicle, in a parking lot. The image may be processed locally or at a server. A vehicle may be identified based on analysis of the image. Further, information regarding the user may be processed to determine another vehicle appropriate for a recommendation. For example, a prompt on a mobile device may suggest a popular model similar to the vehicle being viewed. The system may then provide directions (e.g., augmented reality directions) to the user to direct the user to the vehicle.

Abstract: Systems as described herein may include authorizing the sharing of data and sharing data between a variety of systems. A request to share data may be provided to a first system. The system may create sharing session data using smart contracts executed by a distributed network system. Sharing session data may be stored using a smart contract. A second system may obtain the sharing session data and verify the sharing session based on the execution of the smart contract. On verification of the sharing session, a variety of data may be shared between the systems identified in the sharing session data. The sharing session data may be established between two systems and/or a number of systems. Smart contracts may provide a variety of functions for authorizing the sharing of data between systems. Additionally, encrypted data may be stored and/or obtained using a smart contract.

Abstract: According to certain aspects of the disclosure, a computer-implemented method may be used for determining one or more vehicle recommendations. The method may include receiving data pertaining to a user's internet browsing activity. The received data may be indicative of the user's automotive vehicle preferences. The method may include comparing the received data to a collection of stored vehicle qualities. The method also may include identifying, based on the received data and the comparison of the received data to the collection of stored vehicle qualities, a vehicle characteristic of interest to the user. Using the vehicle characteristic of interest, one or more vehicle recommendations may be determined. One or more vehicle recommendations may be communicated to the user.