Abstract: A method for data distribution includes: receiving a request for data distribution sent from a terminal; searching for raw association network data, wherein the raw association network data includes a set of nodes and a set of edges existing between the nodes; searching for a corresponding user grade according to a user identifier carried in the request for data distribution, and determining a privacy budget parameter corresponding to the user grade; determining the distributing probability distribution corresponding to the raw association network data to be distributed according to a pre-constructed Laplace Model and the determined privacy budget parameter; selecting an arbitrary value within the distributing probability distribution as a distributing probability for each network edge of the set of edges, generating a random number between 0 to 1 for each network edge, comparing the random number to the distributing probability, and distributing the corresponding network edge when the distributing probabilit

Abstract: A method of matching cross-platform data, comprising: receiving a data matching request sent by a terminal; obtaining a group behavior data corresponding to the first user group in the first social network platform, and learning the group behavior data to obtain a group feature distribution function; obtaining associated users of the designated root node users and corresponding behavior data in the second social network platform; learning the behavior data of the root node users, and generating the group feature distribution function after matching the root node users; performing the behavior learning to the behavior data of the associated users; calculating a maximum entropy value of the group feature distribution function after matching the associated users, and determining the associated users corresponding to the largest maximum entropy value as the matching users of the first user group; and regarding the determined matching users as current root node users, determining a next matching user until the det

Abstract: The provided method includes: classifying damage assessing images of a same vehicle portion into one same image set; obtaining keypoint features of each image set, diving every two damage assessing images in each image set into one image group, matching multiple relevant keypoints from the damage assessing images in each image group; calculating a feature point transform matrix of each image, and converting one of the two damage assessing images in each image group to a to-be-verified image which has the same shooting angle as the other damage assessing image in the image group; matching feature parameters of the to-be-verified image with those of the other damage assessing image in the same image group; and generating reminder information, when there are unmatched parameters, to remind the user of frauds of the damage assessing images received from the terminal.

Abstract: The present invention provides a voiceprint recognition method, a device, a storage medium and a background server.

Abstract: A speech recognition method, comprising: acquiring speech data to be recognized; extracting a Filter Bank feature and a Mel-Frequency Cepstral Coefficient (MFCC) feature in the speech data; using the MFCC feature as input data of a trained Gaussian Mixture Model-Hidden Markov Model (GMM-HMM) model, acquiring a first likelihood probability matrix outputted by the trained GMM-HMM model; using the Filter Bank feature as an input feature of a trained long short-term memory (LSTM) model which has a connection unit, acquiring a posterior probability matrix outputted by the LSTM model; using the posterior probability matrix and the first likelihood probability matrix as input data of a trained HMM model, acquiring an second likelihood probability matrix; and acquiring a target word sequence corresponding to the speech data to be recognized from a phoneme decoding network according to the second likelihood probability matrix.

Abstract: A method for processing real estate information comprises steps of: acquiring a target geographical location corresponding to real estate information to be appraised; acquiring all configuration information within a preset range around the target geographical location; determining a score corresponding to each piece of configuration information according to a preset scoring standard; obtaining a standardized eigenvalue by projecting the score determined according to a distance between each piece of configuration information and the target geographical location; and determining an appraised price of a real estate corresponding to the target geographical location by using a real estate price appraisal model according to the standardized eigenvalue

Abstract: A video recording method is disclosed including: extracting every predetermined time period a first image captured by a monitoring camera; performing region detection on the first image to extract areas of interest covering some or all parts of a target object; performing motion area filtering on the areas of interest to select one or more target areas; dividing each target area into multiple sub-areas; extracting every predetermined time period a second image captured by the monitoring camera; comparing an image block located in each sub-area of the second image with that in the same sub-area of the second image previously extracted, to determine whether a motion event has occurred in each sub-area; and controlling the monitoring camera to start video recording from the currently extracted second image when a motion event has occurred in a sub-area. A server, system, and storage medium suitable for the method are also disclosed.

Abstract: A method and system of detecting image tampering, an electronic device and a storage medium. The method includes: A. carrying out block segmentation on a to-be-detected image to segment the to-be-detected image into a plurality of image small fragments, and extracting initial tampering detection features from all the image small fragments; B. encoding the extracted initial tampering detection features with a predetermined encoder to generate complicated tampering features, and determining a tampering detection result corresponding to the to-be-detected image according to the generated complicated tampering features, wherein the tampering detection result includes an image-tampered result and an image-not-tampered result. The disclosure realizes accurate detection for different types and formats of image tampering.

Abstract: The present application provides a method and device for vehicle identification, the method comprises: obtaining a first vehicle image and a second vehicle image, wherein the first vehicle image comprises a first vehicle, and the second vehicle image comprises a second vehicle; extracting a first color feature and a first vehicle type feature of the first vehicle, and extracting a second color feature and a second vehicle type feature of the second vehicle based on a convolutional neural network model; combining the first color feature and the first vehicle type feature into a first vehicle feature, and combining the second color feature and the second vehicle type feature into a second vehicle feature; calculating a similarity parameter between the first vehicle feature and the second vehicle feature; and determining whether the first vehicle is the same one as the second vehicle according to the similarity parameter.

Abstract: A method of searching a group based on a social network includes: receiving a group search request transmitted by a query terminal, wherein the group search request contains a specified query user identification (ID), a group scale and a group coritivity; retrieving a pre-generated social network graph; using the user node corresponding to the query user ID as a starting node to perform search expansion according to the social network graph, and determining a user node having the maximum number of adjacent nodes in each search expansion layer as a group member until the number of determined group members equals to the group scale in the social network graph; a first level of the expansion layer includes the user node, which is an adjacent node of the query user, and the user node included in a next level of expansion layer is an adjacent node of the group member determined by the upper level of the expansion layer; and determining that a group coritivity of the group to be searched is not less than the specif

Abstract: The present invention provides a method and a device for processing question clustering in an automatic question and answering system. The method comprises: receiving a clustering request input by a writer; acquiring a question set to be clustered from a database of unanswered questions based on the clustering request; performing feature extraction on the question set to be clustered with a text feature extraction algorithm to output a question feature set; determining whether the question feature set meets a preset splitting condition; performing segmenting clustering on the question feature set with a segmenting clustering algorithm if the preset splitting condition is met to output at least two question feature subsets; updating the question feature subsets to a question feature set, determining whether the question feature set meets the preset splitting condition; and outputting the question feature set as a clustering class cluster if the preset splitting condition is not met.

Abstract: The present disclosure provides a video compressed sensing reconstruction method, including: step B, after receiving to-be-reconstructed compressed video frames, extracting frame fragments of the compressed video frames according to a predetermined extraction rule; step C, inputting the frame fragments into an input layer of a pre-trained video frame reconstruction model, performing feature abstraction to the frame fragments through multiple hidden layers of the video frame reconstruction model, and building a nonlinear mapping between each frame fragment and a corresponding frame fragment block; and step D, reconstructing the input frame fragments to frame fragment blocks by the hidden layers according to the nonlinear mapping, and outputting the frame fragment blocks by an output layer of the video frame reconstruction model, and generating a reconstructed video based on the reconstructed frame fragment blocks. The present disclosure can render and reconstruct video frames quickly with a high quality.

Abstract: A method of searching a group based on a social network includes: receiving a group search request transmitted by a query terminal, wherein the group search request contains a specified query user identification (ID), a group scale and a group coritivity; retrieving a pre-generated social network graph; using the user node corresponding to the query user ID as a starting node to perform search expansion according to the social network graph, and determining a user node having the maximum number of adjacent nodes in each search expansion layer as a group member until the number of determined group members equals to the group scale in the social network graph; a first level of the expansion layer includes the user node, which is an adjacent node of the query user, and the user node included in a next level of expansion layer is an adjacent node of the group member determined by the upper level of the expansion layer; and determining that a group coritivity of the group to be searched is not less than the specif

Abstract: A method of automatically extracting a validity period of a driving license is disclosed. The method include: extracting candidate contour regions in an image file of a vehicle driving license and selecting from among the candidate contour regions at least one containing an annual inspection validity period; extracting character contours in each selected candidate contour region; acquiring a smallest circumscribed rectangle of each character contour, and dividing the acquired smallest circumscribed rectangles into individual single-character blocks; sorting these single-character blocks according to their positions in the contour region; recognizing a corresponding character of each single-character block; generating a character string representing the annual inspection validity period using the recognized characters based on the sorting; and extracting and taking time data in the character string as the annual inspection validity period of the contour region.

Abstract: A method of automatically extracting a validity period of a driving license is disclosed. The method include: extracting candidate contour regions in an image file of a vehicle driving license and selecting from among the candidate contour regions at least one containing an annual inspection validity period; extracting character contours in each selected candidate contour region; acquiring a smallest circumscribed rectangle of each character contour, and dividing the acquired smallest circumscribed rectangles into individual single-character blocks; sorting these single-character blocks according to their positions in the contour region; recognizing a corresponding character of each single-character block; generating a character string representing the annual inspection validity period using the recognized characters based on the sorting; and extracting and taking time data in the character string as the annual inspection validity period of the contour region.

Abstract: The present invention discloses a method, a system, an electronic device, and a medium for classifying license plates based on deep learning that are applied to an electronic device. The method includes: acquiring at least one photograph sent by a terminal device; preprocessing the acquired photograph such that the preprocessed photograph matches a plurality of input parameters of a pre-trained recognition model; and inputting the preprocessed photograph to the pre-trained recognition model to recognize corresponding vehicle use information of the photograph, and sending the corresponding vehicle use information of the photograph to the terminal device. Thus, with this disclosure, the use of a vehicle in a photograph can be automatically and accurately recognized and further the photographs can be accurately classified, thereby improving the accuracy as well as the efficiency.

Abstract: A video recording method is disclosed including: extracting every predetermined time period a first image captured by a monitoring camera; performing region detection on the first image to extract areas of interest covering some or all parts of a target object; performing motion area filtering on the areas of interest to select one or more target areas; dividing each target area into multiple sub-areas; extracting every predetermined time period a second image captured by the monitoring camera; comparing an image block located in each sub-area of the second image with that in the same sub-area of the second image previously extracted, to determine whether a motion event has occurred in each sub-area; and controlling the monitoring camera to start video recording from the currently extracted second image when a motion event has occurred in a sub-area. A server, system, and storage medium suitable for the method are also disclosed.

Abstract: The provided method includes: classifying damage assessing images of a same vehicle portion into one same image set; obtaining keypoint features of each image set, diving every two damage assessing images in each image set into one image group, matching multiple relevant keypoints from the damage assessing images in each image group; calculating a feature point transform matrix of each image, and converting one of the two damage assessing images in each image group to a to-be-verified image which has the same shooting angle as the other damage assessing image in the image group; matching feature parameters of the to-be-verified image with those of the other damage assessing image in the same image group; and generating reminder information, when there are unmatched parameters, to remind the user of frauds of the damage assessing images received from the terminal.

Abstract: Disclosed are a system, device, method, and readable storage medium for issuing an auto insurance investigation task. The system includes: a task issuance module that acquires associated crowdsourcing parameters of an auto insurance investigation task, determining one or more public investigators matching the investigation task based on a preset first analysis rule and a preset model, and issuing the investigation task carrying the crowdsourcing parameters to mobile terminals of the determined public investigators; a data acquisition module that obtains corresponding investigation data of the investigation task from a mobile terminal of at least one of the determined public investigators who have accepted the task after recognizing the issued investigation task has been accepted; and a data analysis module that analyzes the obtained investigation data based on a preset second analysis rule and finding out the investigation data that conforms to preset conditions as the task result to be adopted.