61 results about "Bipartite graph matching" patented technology

A word alignment apparatus includes a word extracting portion that extracts each word from an example sentence and from a translation sentence thereof, an alignment calculator that calculates at least one of a similarity degree and an association degree between a word in a first language and that in a second language to perform an alignment between words respectively included in the example sentence in the first language and those included in the translation sentence thereof in the second language on the basis of a calculated value, and an optimization portion that optimizes the alignment by performing a bipartite graph matching.

A word alignment apparatus includes a word extracting portion that extracts each word from an example sentence and from a translation sentence thereof, an alignment calculator that calculates at least one of a similarity degree and an association degree between a word in a first language and that in a second language to perform an alignment between words respectively included in the example sentence in the first language and those included in the translation sentence thereof in the second language on the basis of a calculated value, and an optimization portion that optimizes the alignment by performing a bipartite graph matching.

The invention provides an intelligent taxi scheduling system. An operational method of the system includes the steps of first, cellphones of the passengers and drivers send call / availability requests (containing GPS information); second, a server runs a people-car matching algorithm based on bipartite graph matching to match drivers and passengers, and sends scheduling arrangements to the corresponding drivers; third, if the drivers take scheduling, the server sends requests of confirmation to the corresponding passengers; if the drivers do not take scheduling, the second step is repeated; fourth, after picking up the passengers, the drivers send request conformation to the server. The intelligent taxi scheduling system has the advantage that taxies can be efficiently scheduled through the people-car matching algorithm and a breach monitoring mechanism.

The invention discloses a method for matching envelope images. The method comprises the following steps of: respectively representing two envelope images to be matched by using graphs so that the calculation of the degree of similarity between the images is changed into graph matching, and calculating a distance between two graphs by using a bipartite graph matching algorithm based on the minimum weight value. The method comprises the specific steps of segmenting the envelop images, and constructing the graphical representation of the images based on a segmentation result, wherein each vertex of the graph represents an area in the envelope image, and each edge of the graph is used for representing an adjacency relation between two areas. Because the graphical representation of a plurality of images which correspond to the same envelope can be different under the influence of factors such as noise in the acquisition process of the images, a non-accurate graph matching algorithm is adopted in the method. Lots of experimental results show that: the method has relatively higher robustness in illumination, inclining, rotation and the like; and letter information query based on the envelope images can be efficiently realized.

The invention provides a sensor data processing and cooperative prediction method based on edge calculation in the technical field of data processing and edge calculation. The method comprises the following steps: S1, establishing a scene model of a multi-sensor group, a multi-MEC server and an aggregation node; S2, the sensor group is configured with a data node with storage and communication functions to store record values of a plurality of past moments, and abnormal value detection and correction are carried out on data; S3, unloading the task data to the MEC server by the data nodes through bipartite graph matching; S4, performing clustering and fitting by the MEC server by using the received data, and sending the parameters to the aggregation node; and S5, receiving input data of theprediction task and performing comparative analysis on the data and the received parameters by the aggregation node; according to the method, the data node is established at the multiple sensors to unload the data cleaning task, and the data are predicted at the aggregation node, so that the accuracy and robustness are improved, and the time delay and energy consumption are reduced.

The invention discloses a multi-perspective target retrieval method. The multi-perspective target retrieval method includes steps of acquiring a retrieval target input by a user and view sets of objects in database; utilizing the image characteristics extraction algorithm to extract characteristics of the retrieval target and the objects in the database; clustering the view sets by a clustering method after characteristics extraction and extracting representative views of each type; determining corresponding initial weight of each representative view according to scale of the belonging type and updating the weights by means of relation between the representative views and generating the final weights; establishing a weighted bipartite graph by means of the representative views of the two view sets and their weights; seeking the optimal matching of the weighted bipartite graph by the bipartite graph matching algorithm and acquiring similarity between the retrieval target and each object in the database, sequencing and outputting the sequencing result as retrieval results. By the multi-perspective target retrieval method, accuracy of multi-perspective target retrieval is improved.

Described are techniques for determining temporary storage areas for logical volumes to be swapped. Logical volumes may be swapped in a computer system in connection with efforts to improve performance of associated data storage entities in the computer system. As part of the data swapping and physical relocation of logical volumes, temporary storage locations are used. A temporary storage location is associated and used with each logical volume being swapped. Determining a temporary storage area for a logical volume may be made in accordance with particular criteria. A temporary storage area is determined for each logical volume from a list of one or more possible candidate locations. The problem of matching a logical volume to a unique temporary storage area may be represented as a bipartite graph matching problem using solutions, such as the maximum flow, and other techniques to find a match for each logical volume.

The invention provides a network selection method based on weighted optimal bipartite graph matching. The network selection method based on weighted optimal bipartite graph matching comprises the following steps that (1) the parameters of user present service quality, service demands and network performance all serve as input parameters and applied to the network selection process in a cloud processing center; (2) if the number of users is larger than the number of candidate networks, multi-user fair scheduling is conducted firstly; (3) a bipartite graph model is created for the network selection question; (4) the matching degree of the demands and the network performance of each pair of users is calculated, and network selection based on bipartite graph optimal matching is achieved; (5) the network load conditions are detected, and other networks are reselected for the users in an overload network and the users with access being blocked. According to the network selection method based on weighted optimal bipartite graph matching, a heterogeneous network convergence scene is combined with the multi-user scheduling technology, a complicated problem is divided into simple partial problems to be solved, and low-complexity optical network selection integrating the user demand and the network performance is achieved.

The invention discloses a resource allocation method used for a full duplex cellular network physical layer safe scene, aims at a full duplex cellular network where a plurality of upstream users, downstream users and eavesdroppers, adopts BGRA(Bipartite Graph Based Resource Allocation Scheme), constructs a bipartite graph according to a full duplex cellular network, converts the multi-user resource allocation problem into the bipartite graph maximum weight matching problem, an optimal subgraph is a subgraph with the sum of all edge weights being the largest, and through an acquired optical subgraph G' of a bipartite graph, reasonably allocates Resource Blocks (RBs) and power resources. The resource allocation method used for the full duplex cellular network physical layer safe scene can realize mutual cooperation of uplinks and downlinks in the full duplex system, thereby enhancing safety performance of the physical layer; and can also obtain quasi-optimal safety capacity of a full duplex cellular system with relatively low computation complexity, thereby achieving the purpose of improving the system safety capacity.

The embodiment of the invention relates to the technical field of electric vehicle scheduling, in particular to a vehicle scheduling method and device. According to the method, a weighted penalty matrix can be generated based on multiple pieces of obtained order information and multiple pieces of vehicle information; Weighted penalty matrix, an optimal order assignment scheme is found by adoptinga bipartite graph matching algorithm; The embodiment of the invention further provides a vehicle scheduling method and device, for the situation that a plurality of waybills need to be delivered in the order information, the method can carry out delivery route planning, and then accurate and efficient scheduling of vehicles is achieved.

The invention provides a disjoint-view object matching method based on a corrected weighted bipartite graph. The method relates to the field of computer vision. The method expresses a disjoint-view object matching problem as a maximum posterior probability problem, so that an object observation model and time-space constraints of a surveillance network are combined, and the maximum posterior probability problem is resolved through solving the maximum weight matching of a weighted bipartite graph. To solve the problem that construction of a common weighted bipartite graph is liable to introduction of incorrect matching, the method provides a corrected weighted bipartite graph construction method based on an adaptive threshold, so that incorrect matching is prevented from being introduced during construction of the weighted bipartite graph as much as possible. Aimed at the defect of a conventional KM method that the amount of computation is too large during large-scale weighted bipartite graph matching problem solving, the method brings forward a MH sampling-based method for approximating and solving the maximum weight matching of the weighted bipartite graph, so that a disjoint-view object matching relationship is obtained.

The invention discloses a cell tracking method based on global and local optimum. According to the method, independent regions are obtained through initial segmentation by means of ellipse fitting, and adherent cells in need of segmentation are identified; then a wavelet transformation method is used to carry out further segmentation; the center of mass of each cell subjected to segmentation is calculated and used as a unique characteristic of the cell; a bipartite graph matching method is used for inter-frame correlation of the cells, then cell shifting-in, shifting-out, division and shielding events are identified, matching is iterated and incomplete cell track segments are obtained; and through analysis, identification and correction of cell track segments, finally a complete cell track is generated based on local optimum. The method utilizes cell location information to achieve sub-cell relation of cell division and has good effect on different data sets.

The invention discloses a privacy-preserving spatial crowdsourcing bidding method, which comprises the following steps: according to the task information submitted by the requester and the status information submitted by the worker, carrying out the task assignment based on the reverse auction process, and formalizing the winning bidder selection problem in the auction process as a n:1 weighted bipartite graph matching problem with 0-1 knapsack restriction; using the optimal auction theory to calculate the corresponding payment value of the winning bidder, which is the critical value of the winning bidder; when completing the task assignment process, introducing a semi-honest third party to generate the encrypted secret key for the spatial crowdsourcing system to protect the privacy of theworker by using the homomorphic encryption technology. Competitive task assignment is realized, which improves the effectiveness of spatial crowdsourcing system and ensures the privacy of workers, and motivates workers to actively participate in the spatial crowdsourcing system. The method has good advancement and practicability.

The invention provides an information recommendation method and system based on multi-path optimization matching. Historical payment information, power utilization information, recommendation serviceinformation and service recommendation information of each client are acquired; based on the payment behavior data and the power consumption behavior data, the data is clustered by using a fuzzy C-means clustering algorithm, clustering features suitable for analyzing customer behaviors from the data are selected, customer behavior theme tags are constructed, and different types of power customer behavior mode portraits are achieved; the electricity consumption behavior data and the payment behavior data of the client are clustered, behavior characteristics are analzyed, behavior label characteristics are set, business characteristic attributes are described, a business label set is formulated, and business portrait construction is completed; according to the method, a bipartite graph of aclient label set and a service label set is constructed, a Hopcroft-Karp algorithm with the maximum bipartite graph matching is applied to matching of clients and services, the matched clients are found, and service information recommendation is completed.

The invention provides a painting rendering method based on colour feature study. The method comprises the following steps of: firstly, definitely defining some colour features for deciding the colour motion and colour style of a reference template mathematically; providing a study mechanism based on optimum with respect to the features, abstracting the optimization problem into a bipartite graph matching model to solve the problem by adopting a classical KM algorithm. The invention provides an after-treatment technique based on image division to ensure the continuous result in the space with respect to some pseudo boundary effect probably occurring in the result. Finally, in the drawing processing, the invention provides a new colour mixing model on the traditional framework to control the drawing accuracy better without selecting a great amount of parameters.

The invention provides a cross-platform association detection method for firmware vulnerability, which improves the accuracy and efficiency of the existing cross-platform firmware vulnerability association detection method, combines kNN with SVM, and achieves a better compromise between accuracy and efficiency. Based on the function attribute control flow graph, the bipartite graph matching algorithm is used to transform the function matching problem into the graph structure similarity computation problem, and the penalty term is added to the original algorithm, which improves the accuracy ofaccurate matching. The weighted Euclidean distance and the weighted Markov distance are used to improve the detection efficiency.

The invention discloses a partitioned wireless sensor network repair method based on mobile relay scheduling and mainly solves the problems of low connection success rate and high connection cost in the prior art. The method includes implementation steps: 1, setting one side between any two border sensors in different partitions; 2, respectively calculating the weight of each side to obtain an optimal position of a mobile relay node in connection of each side; 3, sequentially adding the sides according to the sequence of the weights from small to large until a whole partitioned network is connected, and recording the added sides and the corresponding optimal position of the mobile relay node; 4, calculating to obtain a mobile relay node scheduling scheme by means of bipartite matching, and connecting each partitioned network according to the scheme. Simulation results show that the partitioned wireless sensor network repair method based on mobile relay scheduling is higher in connection success rate and lower in connection cost as compared with other existing methods in partitioned wireless sensor network repair, and the method can be used for repairing wireless sensor networks in dangerous or harmful environments.

The invention relates to the technical field of intelligent scheduling, in particular to a logistics scheduling method and device, and the method comprises the steps: obtaining a plurality of deliverymen to be scheduled and a plurality of orders to be distributed; for each deliveryman, obtaining an influence factor related to the deliveryman; determining a relationship weight between the deliveryman and each order based on the influence factor; determining an optimal order assignment scheme by adopting a bipartite graph matching algorithm based on the relationship weight, and matching each order in the optimal order assignment scheme with the deliveryman; and for each order, assigning the order to a deliveryman matched with the optimal order assignment scheme in the optimal order assignment scheme. According to the logistics scheduling method, the relationship weight between the deliveryman and each order is determined through the influence factors related to the deliveryman, and the bipartite graph matching algorithm is adopted to determine the optimal order assignment scheme based on the relationship weight, so that the matching success rate and the logistics scheduling efficiency can be improved.

The invention provides a PCB image color migration device and method based on clustering analysis, and the device comprises an image collection module which obtains a source image and a target image;a RGB color image acquisition module which is used for respectively acquiring RGB color images converted from the source image and the target image; a color space conversion module which converts theRGB color image into an LAB color image; a color clustering module which is used for setting and clustering the LAB color images by utilizing the number of color clusters to generate a color cluster category list; a color cluster matching module which performs PCB bipartite graph matching on the list of the source image and the target image to obtain a matching result; a color mapping module whichcalculates a transformation matrix according to a matching result, and maps the LAB color image to a new color according to the matrix; and a color space inverse transformation module which convertsthe mapped color into an image after RGB color migration. According to the device, colors in an image are divided into different categories by clustering, color migration is carried out on the colorsof the different categories respectively, and a good image registration effect is achieved.

The invention belongs to the field of intelligent information systems, and particularly relates to an official document approver intelligent recommending method based on an official document fragmentand the bipartite graph matching. The method includes the steps of firstly, extracting feature information of an official document and property information of approvers; secondly, calculating the matching rate of the official document and a scoring matrix of the official document approvers; thirdly, determining the optimum approver according to the overall official document matching rate, and determining a recommending approver group in combination with a bipartite graph matching strategy. By means of the method, the intelligence and efficiency of the electronic official document approval process can be effectively improved.

The invention relates to a mutual evaluation method for the homework of students during the online course and belongs to the field of computer application. The method comprises the steps of extracting the features of the learning records of students, calculating the similarity between a homework grading student and a to-be-graded student, assigning the homework through the bipartite graph matching process, solving out an optimal solution for the bipartite graph matching process, and figuring out an optimal homework assignment scheme for the mutual evaluation of the homework. According to the technical scheme of the invention, the homework assignment problem is converted into the graph theory problem. Meanwhile, the problem is solved out based on the related algorithms of the graph theory. The obtained outcome of the solution fully considers the similarity between the homework grading student and the to-be-graded student from a global perspective. Therefore, students most similar in learning habit and learning level are matched to the greatest extent. At the same time, two parties that participate the mutual evaluation process are similar in learning level and learning habit as much as possible.

The invention discloses a time difference of arrival based multiple source localization Taylor slack-partial iteration algorithm which comprises the steps of firstly constructing an original problem model; slacking non-convex constraint of an original problem to convex constraint by means of a Taylor slack method, slacking an integer variable to a continuous variable; obtaining an initial point required for the algorithm through coarse semi-definite relaxation and secondary cone relaxation; obtaining an integer solution by means of bipartite matching; and introducing the obtained integer solution into the model, and calculating the optimal estimated coordinate value of each to-be-positioned object. According to the algorithm of the invention, the non-convex constraint is converted to convex constraint by means of Taylor slack; and furthermore discrete the integer variable is slacked to a continuous variable, thereby greatly reducing complexity of the original problem, improving solvability of the problem. Under a precondition that the initial point is properly selected and base station are laid reasonably, a whole-domain optical solution can be obtained.

The invention provides a method and device for calculating the matching relation between input three-dimensional bodies, and the method comprises the steps: obtaining two input three-dimensional bodies, generating a sampling point set which is uniformly distributed on the surfaces of the bodies, and calculating the matching relation between sampling points; identifying abnormal matching point pairs of the sampling point set; dividing the wrong matching pairs into a plurality of sub-regions by utilizing a consistency segmentation result between the input bodies, modeling matching between the sub-regions into a bipartite graph matching problem, solving matching between the sub-regions, and obtaining an improved sampling set matching relationship; and matching according to the sampling set and generating a global matching relationship of the body surface based on a function mapping framework. According to the method provided by the embodiment of the invention, the matching relationship between the sampling points on the surface of the input body can be calculated in a short time, the global dense matching is expanded, the body matching purpose is realized, the calculation time is shortened, and meanwhile, the calculation accuracy is ensured.

Embodiments of the invention provide an image style brush realization method and device. The method comprises the following steps of: obtaining matched corresponding points of an input image and a reference image according to density correspondence between the input image and the reference image; determining a first superpixel set of the input image and a second superpixel set of the reference image according to the matched corresponding points, and further determining a superpixel bipartite graph; carrying out bipartite graph matching on the superpixel bipartite graph so as to determine mutually matched superpixel pairs in the first superpixel set of the input image and the second superpixel set of the reference image; and carrying out color conversion on superpixels of the input image according to a first color space and the superpixel pairs so as to obtain a result image. According to the method and device, style conversion is carried out on the input image according to multiple style elements of the reference image so as to obtain the result image, so the multiple style elements in the reference image are directly and completely converted onto the input image, the visual effect related to the color, greyscale and contrast ratio of the input image is changed, and then the result image further has the style of the reference image.

The invention relates to a multichannel wireless network scheduling method supporting information age optimization, and belongs to the technical field of wireless networks. According to the method, aiming at scenes of a plurality of source nodes and a plurality of target nodes in a multi-channel wireless network, links are scheduled by time slot by time slot by taking average information age in the network as an optimization target; converting an information age optimization problem into optimization of Lyapunov drift expected by the information age, converting a multi-channel conflict probleminto a bipartite graph matching problem, and obtaining a conflict-free scheduling scheme in the multi-channel wireless network by adopting a Kuhn-Munkres algorithm. According to the invention, scheduling is carried out on a plurality of channels, the utilization rate of network resources is improved, and the average information age of the network is optimized; meanwhile, the target node does notneed to acquire the data packet generation time of the source node in advance, so that the energy consumption caused by interaction between the nodes is reduced.

The invention discloses a GPU multi-task scheduling system and a method based on Kernel merging. Including task analysis module, Kernel merge module, task scheduling module and task storage queue. Theuser submits the GPU task to the task storage queue, the task analysis module calculates the merging acceleration ratio between tasks, the task scheduling module calculates the optimal merging scheduling sequence, and delivers it to the Kernel merging module for merging execution, so as to obtain the maximum task throughput; The invention adopts the maximum matching of the general graph to calculate the optimal consolidation scheduling order. The task merge acceleration ratio is calculated by task analysis module. Secondly, the directed graph is constructed according to the acceleration ratioof task merging. The optimal task consolidation scheduling order is calculated by bipartite graph matching algorithm. Task groups are sequentially scheduled to complete task calculations. The invention completes the design details of the function, realizes the algorithm and the coding work, and improves the resource utilization rate of the GPU under the multi-task.

An exemplary embodiment of system, computer-accessible medium and method for comparing a first genome to a second genome. For example, a first genome may be compared to a second genome by building a first library for the first genome and a second library for the second genome, providing a plurality of matches between elements in the first library common to elements in the second library, ranking each match to determine a likelihood of similarity between the common elements in the first and second libraries; and associating matches having a predetermined likelihood. The association may be performed efficiently by a stable marriage procedure.

The invention discloses a bipartite graph based in-vehicle network distributed storage method. According to the bipartite graph based in-vehicle network distributed storage method, a distributed storage problem is firstly modeled, and bipartite graph matching is performed, so that optimal in-vehicle network distributed storage of in-vehicle request identification information sent by each in-vehicle node can be achieved under different conditions, and in-vehicle network can respond to maximum in-vehicle request identification information; subsequently, repeated network information stored by roadside units is cleared, resource waste generated by the fact that multiple roadside units respond to the same in-vehicle request identification information is avoided, and meanwhile, in-vehicle request identification information which is met is not affected; finally, in-vehicle request identification information which is not met is collected, and secondary allocation is performed on spare storage space obtained by clearing the roadside units until each roadside unit has no spare storage space, or all the in-vehicle request identification information received by the roadside units is responded, or remaining in-vehicle request identification information cannot be met; a storage resource utilization rate and a data response data are increased, and data service qualities of an in-vehicle network are guaranteed.

The invention relates to an online cross-scale multi-fluid target matching and tracking method, which comprises the following steps of: extracting an associated object by adopting a sliding window, matching and tracking specific characteristics on an associated object image, and extracting fluid target characteristics of different scales; selecting basic characteristic parameters for characteristic extraction according to fluid target characteristics of different scales; calculating a composite association weight according to the feature information of the two continuous frames, extracting spatial association and time association information between different body targets through the composite association weight, and constructing a weighted bipartite graph based on the two adjacent framesbased on the association information; performing online target matching by adopting a sparse weighted bipartite graph matching algorithm, and constructing a sparse weighted bipartite graph based on the matched target; and performing target tracking and trajectory prediction by adopting a Kalman filtering algorithm based on the constructed sparse weighted bipartite graph. According to the invention, the multi-fluid target matching tracking precision can be effectively improved; the running time of the method is reduced to the second level, and the online algorithm requirement is met.