Abstract: Embodiments of the disclosure provide systems and methods for processing a transportation service request. An exemplary system may include a communication interface configured to receive the transportation service request from a terminal device. The system may further include at least one processor. The at least one processor may be configured to generate a passenger score based on the received transportation service request using a first machine learning model trained with sample passenger data associated with past impacted drivers. The at least one processor may further be configured to generate a trip score based on the generated passenger score and the received transportation service request using a second machine learning model trained with sample trip data associated with the past impacted drivers. The at least one processor may also be configured to allow or block the received transportation service request based on the generated trip score.

Abstract: The present disclosure provides a system for improving security. The system may identify a query associated with a user account, and access an ID graph database to obtain an ID graph relating to the user account by a database driver. The system may also determine whether the user account is a target account type based at least on the ID graph. The ID graph may include a plurality of nodes and a plurality of edges. Each of the plurality of edges may connect two nodes. Each of the plurality of nodes may include at least one of a register ID, a login ID, a payment ID, a background check ID, or a face ID. Each edge that connects two nodes may include at least one of a user type associated with the two nodes, a timestamp when the edge is connected, or source information of the edge.

Abstract: Embodiments of the disclosure provide systems and methods for reviewing performance of computer models for safety analysis in transportation services. The exemplary system includes a communication interface configured to receive log data associated with at least one reported safety event. The log data includes one or more computer models used for predicting the reported safety event and associated with a first feature pattern and a first model performance. The system further includes at least one processor configured to extract features from the log data and determine a second feature pattern and a second model performance of the computer models. The at least one processor is also configured to detect a change in feature pattern based on the first feature pattern and the second feature pattern or a performance degradation based on the first model performance and the second model performance, and to generate an alert to upgrade the computer models.

Abstract: A system may include at least one computer-readable storage medium including a set of instructions for locating a wireless device having wireless fidelity (WiFi) capability, and at least one processor in communication with the computer-readable storage medium, wherein when executing the set of instructions, the at least one processor is directed to: obtain a positioning request from the wireless device, the wireless device is in communication with at least one WiFi network; obtain WiFi data from the wireless device; and determine a default location associated with the WiFi data as a location of the wireless device.

Abstract: The present disclosure relates to a system and a method for performing instance segmentation based on semantic segmentation that is capable of (1) processing HD images in real-time given semantic segmentation; 2) delivering comparable performance with Mask R-CNN in terms of accuracy when combined with a widely-used semantic segmentation method (such as DPC), while consistently outperforms a state-of-the-art real-time solution; (3) working flexibly with any semantic segmentation model for instance segmentation; (4) outperforming Mask R-CNN if the given semantic segmentation is sufficiently good; and (5) being easily extended to panoptic segmentation.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for ranking alternative destination recommendations are provided. One of the methods comprises: receiving a trip request comprising an origin and an initial destination; determining one or more alternative destinations based on one or more features of the initial destination; for each of the alternative destinations, determining, based on a machine-learning classifier, a probability for the rider to select a trip option from the origin to the alternative destination, where the machine-learning classifier is trained to accept input comprising one or more attributes of the trip option and generate output comprising the probability for the rider to select the alternative destination; generating a score for each of the alternative destinations based at least on the probability; and ranking, by the computing device of the ridesharing platform, the alternative destinations based on the scores.

Abstract: The present disclosure relates to systems and methods for determining a predicted distribution of future transportation service time point. The systems may perform the methods to obtain historical service time points of transportation service requests occurred in a predetermined region; determine a variance of the historical service time points; determine a predicted distribution of future transportation service time point in the predetermined region based on the variance; and store the predicted distribution in a database.

Abstract: A method for displaying a smooth movement of a vehicle on a map may include obtaining a route, a last real-time location of the vehicle, and a last uploading time point. The method may also include obtaining driving data of one or more neighboring vehicles and determining a predicted location of the vehicle at a prediction generating time point. The method may further include displaying a smooth movement of the vehicle from the last real-time location to the predicted location on a map. A method for displaying a driving path of a vehicle on a map may include obtaining a request for displaying a driving path of a vehicle, location information of the vehicle, and scene related information associated with the driving path. The method may further include verifying the location information based on the scene related information and displaying the driving path of the vehicle on a map.

Abstract: A method may include receiving, from a first application installed in an electronic device, a first request for accessing a first set of contents associated with a second application. The method may include obtaining a request time stamp and a content pointer associated with the first set of contents. The method may include placing the link information to a predetermined storage space in the electronic device. The method may include invoking the second application based on the content pointer and obtain an invoking time stamp. The method may include comparing a time interval between the request time stamp and the invoking time stamp to a predetermined time threshold. The method may include accessing the first set of contents in the second application according to the content pointer in response to a determination that the time interval is less than the predetermined time threshold.

Abstract: A computer-implemented method for domain analysis comprises: obtaining, by a computing device, a domain; and inputting, by the computing device, the obtained domain to a trained detection model to determine if the obtained domain was generated by one or more domain generation algorithms. The detection model comprises a neural network model, a n-gram-based machine learning model, and an ensemble layer. Inputting the obtained domain to the detection model comprises inputting the obtained domain to each of the neural network model and the n-gram-based machine learning model. The neural network model and the n-gram-based machine learning model both output to the ensemble layer. The ensemble layer outputs a probability that the obtained domain was generated by the domain generation algorithms.

Abstract: Embodiments of the disclosure provide systems and methods for verifying digital payments for a payment platform. The system includes a communication interface configured to receive service data associated with a transaction from a terminal device associated with a user of the payment platform. The system further includes at least one processor configured to automatically determine whether an authentication is waived for the transaction based on the received service data and a blacklist generated using a machine learning model. The blacklist includes a list of suspicious users and transaction behaviors. The at least one processor further configured to approve the transaction without requesting user authentication information from the terminal device when the authentication is waived. The at least one processor also configured to request the user authentication information from the terminal device and validate the user authentication information when the authentication is not waived.

Abstract: Embodiments of the disclosure provide methods and systems for determining a position of a terminal device. The system may include a receiving module configured to receive current position information associated with the terminal device, the current position information including one or more positions indicative of the present location of the terminal device. The system may further include an acquisition module configured to acquire historical position information associated with the terminal device, said historical position information being separated from the current position information by a predetermined time interval. The system may further include a determination module configured to determine, based on the historical position information, an actual position of the terminal device from the current position information.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for security analysis are provided. One of the methods includes: determining a data risk value for data of an endpoint based on a number of classified files within the data and a type of classified files within the data; determining an endpoint risk value for the endpoint based on a user risk value and a cyber security risk value; determining a channel risk value for a set of channels through which the data is conveyable by the endpoint based on a number of channels within the set of channels and a type of channels within the set of channels; and rendering a map showing a security risk level of the endpoint, wherein the security risk level is based on the data risk value, the endpoint risk value, and the channel risk value.

Abstract: The present disclosure relates to a method and system for monitoring on route transportations. The method includes obtaining a driving route of a target vehicle; obtaining a reference position on the driving route away from a first current position of the target vehicle; determining a second current position of the target vehicle after a reference time; determining a distance between the second current position and the reference position is greater than a preset distance; and sending a signal to a target terminal indicating that the target vehicle is off-route.

Abstract: The present disclosure discloses an order allocation method. The method may include: receiving orders and extracting order information; extracting service provider information and obtaining features of service providers; determining whether the order information matches the features of the service providers, or determining whether the features of the service providers satisfy a preset condition to generate a determination result; ranking the service providers based on the determination result; generating orders to be allocated; and allocating the orders to be allocated to the service providers based on the ranking. The present disclosure also discloses an order allocation system that can perform the method above.

Abstract: The present disclosure relates to systems and methods for providing online to offline services. The systems and methods may obtain a plurality of historical positions of a user terminal within a first predetermined time period in a plurality of days. The systems and methods may identify at least one candidate area based on the plurality of historical positions of the user terminal. The systems and methods may identify one or more of the at least one candidate areas as one or more active areas of the user terminal. The systems and methods may further provide data associated with one or more service requests relating to the one or more active areas to a customer application executed by the user terminal.

Abstract: Systems and methods for speech recognition are provided. The method may include obtaining a plurality of candidate recognition results of speech information uttered by a user and a plurality of preliminary scores corresponding to the plurality of candidate recognition results, respectively. The method may further include, for each of the plurality of candidate recognition results, extracting one or more keywords from the candidate recognition result and determining at least one parameter associated with the one or more extracted keywords. The method may further include, for each of the plurality of candidate recognition results, generating an updating coefficient based on the at least one parameter and updating the preliminary score based on the updating coefficient to generate an updated score. The method may further include determining, from the plurality of candidate recognition results, a target recognition result based on the plurality of updated scores.

Abstract: A method configured to implemented on at least one map processing device for determining new roads on a map includes obtaining a first road network image of a region, the first road network image including a first plurality of roads. The method also includes determining a second road network image of the region based on a map of the region, the second road network image including a second plurality of roads that are not present in the first road network image. The method further includes determining a third road network image by concatenating the first road network image and the second road network image. The method still further includes determining a fourth road network image of the region by processing the third road network with at least one convolution layer, the fourth road network including the second plurality of roads.

Abstract: The present disclosure relates to a system and method for determining an optimized route for a carpool service. The method may include stringing a plurality of nodes to generate a plurality of first candidate paths. The method may also include determining a geographical length for each of the plurality of first candidate paths based on geographical distances between any two of the plurality of nodes. The method may also include determining one or more second candidate paths among the plurality of first candidate paths based on the geographical length for each of the plurality of first candidate path. The method may also include determining the navigation length for each of the one or more second candidate paths. The method may also include determining a target path among the one or more second candidate paths based on the navigation length.

Abstract: The present disclosure provides a method and system for analyzing and managing transportation. The method may include generating, for each of a plurality of geographic regions, a first graph representation based on transportation data relating to transport activities within the geographic region. The method may also include obtaining, for any two of the plurality of geographic regions, via a graph kernel based algorithm, a first similarity indicator measuring a similarity between the first graph representations of the any two of the plurality of geographic regions. The method may further include grouping, based on the first similarity indicators, the plurality of geographic regions into a plurality of groups. The method may also include, for each of the plurality of groups, identifying at least one featured transportation type of the group and associating a strategy to the group to promote or restrict transport activities of the at least one featured transportation type of the group.