Abstract: Provided are a navigation path planning method and apparatus, a device, and a storage medium. The navigation path planning method includes planning at least two available navigation paths for each target user of at least two target users in a target region; and determining a global passing feature of the target region and selecting, according to the global passing feature of the target region, one available navigation path from the at least two available navigation paths corresponding to each target user to serve as a recommended navigation path to be recommended to each target user.

Abstract: The present application discloses a method and apparatus for acquiring point-of-interest (POI) state information, a device and a computer storage medium, and relates to the field of big data. An implementation includes acquiring a text containing POI information in a preset time period from the Internet; and identifying the text using a pre-trained POI-state identifying model to obtain a binary group in the text, the binary group including a POI name and the POI state information corresponding to the POI name; wherein the POI-state identifying model performs label prediction of the POI name and a POI state on a word sequence corresponding to the text, and label prediction results of the POI name and the POI state are aligned to obtain the binary group. With the present application, a human cost may be saved, and timeliness and accuracy may be improved.

Abstract: The present application discloses a method and apparatus for determining a route, a device and a computer storage medium, and relates to the field of big data.

Abstract: A method of updating a road information, an electronic device, and a storage medium, which relate to an artificial intelligence technology field, in particular to fields of computer vision, deep learning, big data, high-definition map, intelligent transportation, automatic driving and autonomous parking, cloud service, Internet of Vehicles and intelligent cabin technologies. The method includes: processing image data corresponding to a target road region to obtain a set of first road lines; obtaining a set of second road lines according to a trajectory map corresponding to the target road region; calibrating the set of first road lines by using the set of second road lines to obtain a set of third road lines; combining the set of third road lines and a set of historical road lines corresponding to the target road region to obtain a combination result; and updating the set of historical road lines according to the combination result.

Abstract: A method for processing a map, an electronic device, and a storage medium, which relate to a technical field of computer technology, in particular to computer vision technology and high-definition map technology. The method includes: segmenting a first road line to obtain a plurality of first sub-road lines, wherein the first road line is obtained according to a segmentation mask for an image, and the image corresponds to a target region; segmenting a second road line to obtain a plurality of second sub-road lines, wherein the second road line is obtained according to a trajectory information corresponding to the target region; and determining a target road line according to first similarities between the plurality of first sub-road lines and the plurality of second sub-road lines.

Abstract: A method for processing behavior data, a method for controlling an autonomous vehicle, apparatuses thereof, a device, a storage medium, a computer program product, and an autonomous vehicle are provided. The method includes: acquiring historical driving data, the historical driving data comprising lane-level navigation data; and performing data mining on the historical driving data to obtain driving feature information, the driving feature information comprising at least one of: a lane-change position feature, a traveling speed feature, or a traveling path feature.

Abstract: The present disclosure provides a route planning method, apparatus, device and computer storage medium and relates to the technical field of big data. A specific implementation solution is: obtaining real-time traffic flow feature data of a road network; predicting state change risks of the road segments in the road network with the real-time traffic flow feature data of the road network to obtain state change risk information of the road segments; performing route planning with the state change risk information of the road segments. In the present disclosure, considerations of state change risks of road segments are integrated into the route planning so that the route is planned by globally considering the state change risks that the user might face upon passing by the road segments, thereby improving the quality of the planned route and the user's experience.

Abstract: The present disclosure discloses a method, apparatus and electronic device for early-warning, relates to the field of internet of vehicle and used for an intelligent traffic scenario. The specific implementations are: determining a target object crossing a road at a current moment, the road crossed by the target object being a first road; determining a target area based on a location of the target object; determining a target vehicle on the first road based on locations of vehicles on the first road as well as the target area; and sending an early-warning message to the target vehicle. It is using the locations of vehicles on the first road as well as the location of the target object crossing the road to determine the target vehicle during determination of the target vehicle among the vehicles on the first road, in order to send early-warning message to the target vehicle to achieve early-warning of the target vehicle and increase precision of the early-warning.

Abstract: Provided are a voice packet recommendation method and apparatus, a device and a storage medium, relating to intelligent search technologies. The solution includes constructing a first video training sample according to first user behavior data of a first sample user in a video recommendation scenario and first video data associated with the first user behavior data; constructing a user training sample according to sample search data of the first sample user and historical interaction data about a first sample voice packet; pretraining a neural network model according to the first video training sample and the user training sample; and retraining the pretrained neural network model by using a sample video and sample tag data which are associated with a second sample voice packet to obtain a voice packet recommendation model. With the solution, the neural network model can be trained in the case of cold start so that the neural network model can recommend a voice packet automatically in the case of cold start.

Abstract: A route planning method includes: receiving a route planning request including information of a starting position and information of a destination position; planning a route from the starting position to the destination position based on conditions about a road including a physical isolation belt; sending a route planning result, the conditions about a road including a physical isolation belt are fused into the route planning.

Abstract: The present application discloses a method and apparatus for extracting a geographic location point spatial relationship, and relates to the field of big data technologies. A specific implementation solution is as follows: determining geographic location point pairs included in real-scene images by performing signboard recognition on the real-scene images collected by terminal devices; acquiring at least two real-scene images collected by the same terminal device and including the same geographic location point pair; and determining a spatial relationship of the same geographic location point pair by using shooting parameters of the at least two real-scene images. The geographic location point spatial relationship extracted through the present application has higher accuracy and a coverage rate.

Abstract: Provided are a voice packet recommendation method and apparatus, a device and a storage medium. The method includes selecting at least one target display video for a user from among candidate display videos associated with voice packets and using voice packets to which the at least one target display video belongs as candidate voice packets; selecting a target voice packet for the user from among the candidate voice packets according to attribute information of the candidate voice packets and attribute information of the at least one target display video; and recommending the target voice packet to the user.

Abstract: A method and an apparatus for recommending a travel mode, an electronic device; and a storage medium are provided. An implementation is: receiving a request from a user for querying a first point of interest; analyzing a travel type of the user based on the request; obtaining an alternative travel mode based on the travel type in combination with user information; calculating a travel cost corresponding to the alternative travel mode; and recommending at least one travel mode for the user according to the travel cost.

Abstract: The present disclosure discloses a broadcast style determination method and apparatus, a device and a computer storage medium, and relates to voice and deep learning technologies in the field of artificial intelligence technologies. A specific implementation solution involves: performing named entity recognition on broadcast text to obtain at least one named entity; acquiring domain knowledge corresponding to the at least one named entity; and performing sentiment analysis by using the broadcast text and the domain knowledge, to determine a broadcast style of the broadcast text.

Abstract: The present disclosure discloses an intelligent voice interaction method and apparatus, a device and a computer storage medium, and relates to voice, big data and deep learning technologies in the field of artificial intelligence technologies.

Abstract: The present disclosure provides a question answering method and apparatus for query information. The method may include: receiving query information input by a user, and analyzing a query target comprised in the query information; recalling candidate answers from a pre-generated knowledge graph based on the query target, where the knowledge graph is constructed based on inherent data in a map database and dynamic data of historical users, and the dynamic data includes at least one of comment data, search data, or spatiotemporal big data; and returning, in response to that there is a target answer whose matching degree with the query target exceeds a preset threshold in the candidate answers, the target answer to the user.

Abstract: The present disclosure provides a method and apparatus for automatically producing map data. The method includes: performing track rectification on crowdsourcing tracks based on corresponding standard tracks, and locating each map element included, based on depth information of track point images included in the rectified crowdsourcing tracks; comparing a latest map element obtained based on the rectified crowdsourcing tracks locating and an old map element at a corresponding locating position using a pre-built entity semantic map; determining, in response to a change in the latest map element compared to the old map element, a target processing method according to a processing standard of a changed map element pre-abstracted from a map element update specification; and processing the latest map element according to the target processing method to obtain a processed latest map.

Abstract: A method is provided.

Abstract: A method for sorting geographic location points, a method for training a sorting model and corresponding apparatuses are disclosed, which relates to the technical field of big data. A specific implementation solution is: receiving a query request for geographic location points of a vertical class from a user; inputting candidate geographic location point data of the vertical class into a preference model of the user, to obtain a preference score of the user for each candidate geographic location point; inputting the preference score of the user for each candidate geographic location point into a sorting model as one of sorting features of each candidate geographic location point, to obtain a sorting score of each candidate geographic location point; and determining, according to the sorting score of each candidate geographic location point, a query result returned to the user.

Abstract: Technical solutions relate to the field of big data technologies. A technical solution includes: pre-training a time series prediction model using first historical regional heat data; and taking second historical regional heat data as a second support set, and further training the time series prediction model using the second support set to adjust model parameters, so as to obtain the regional heat prediction model; and the regional heat prediction model is configured to predict a second query set, and the second query set includes regional heat at a prediction time.