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33 results about "Similitude" patented technology
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Similitude is a concept applicable to the testing of engineering models. A model is said to have similitude with the real application if the two share geometric similarity, kinematic similarity and dynamic similarity. Similarity and similitude are interchangeable in this context.
Method and device for encoding a score of semantic and spatial similarity between concepts of an ontology stored in hierarchically numbered trellis form
InactiveUS7743010B2Knowledge representationSpecial data processing applicationsSemantic featureInformation retrieval
A method of calculating and encoding a score of semantic and spatial similarity between concepts of an ontology stored in hierarchically numbered trellis form, in which the score (NSSij) is calculated and encoded (1) for each concept (Ci) with respect to a central concept (Cj), taken two-by-two, by convergence relative to their common semantic characteristics respectively by separation according to their distance. The method is applicable to the consultation of ontologies representative of knowledge in the technical or non-technical domain.
Owner:ORANGE SA (FR)
Program similarity detection method and device, electronic equipment and storage medium
PendingCN112257068AQuick filterFind out quicklyPlatform integrity maintainanceProgram fragmentAlgorithm
The invention discloses a program similarity detection method and device, electronic equipment and a storage medium, and the method comprises the steps: extracting a source function and correspondingfunction basic information from a preset source program, and generating a disassembly instruction text; screening a preset target program based on the function basic information and the disassemblinginstruction text to obtain a potential similarity function, and determining a target source function; splitting the target source function into a plurality of source program fragments; splitting the potential similarity function into a plurality of target program fragments; respectively calculating the similarity between any source program fragment and the target program fragment to obtain a similarity score; determining the number of similar target program fragments of which the similarity score reaches a first preset threshold; determining the potential similarity function of which the number of the similar target program fragments reaches a second preset threshold value as a similarity function; and judging whether the source program and the target program have an association relationship or not according to the number of the similarity functions. The technical problems of low analysis speed and low analysis accuracy in the prior art are solved.
Owner:ELECTRIC POWER RESEARCH INSTITUTE, CHINA SOUTHERN POWER GRID CO LTD +1
Method and device for encoding a score of semantic and spatial similarity between concepts of an ontology stored in hierarchically numbered trellis form
InactiveUS20080010260A1Knowledge representationSpecial data processing applicationsSemantic featureDegree of similarity
A method of calculating and encoding a score of semantic and spatial similarity between concepts of an ontology stored in hierarchically numbered trellis form, in which the score (NSSij) is calculated and encoded (1) for each concept (Ci) with respect to a central concept (Cj), taken two-by-two, by convergence relative to their common semantic characteristics respectively by separation according to their distance. The method is applicable to the consultation of ontologies representative of knowledge in the technical or non-technical domain.
Owner:ORANGE SA (FR)
Adaptive robustness certification against adversarial examples
PendingUS20220180172A1Minimize possible overlapImprove robustnessCharacter and pattern recognitionMachine learningCluster algorithmRobustification
Adaptive verifiable training enables the creation of machine learning models robust with respect to multiple robustness criteria. In general, such training exploits inherent inter-class similarities within input data and enforces multiple robustness criteria based on this information. In particular, the approach exploits pairwise class similarity and improves the performance of a robust model by relaxing robustness constraints for similar classes and increasing robustness constraints for dissimilar classes. Between similar classes, looser robustness criteria (i.e., smaller ϵ) are enforced so as to minimize possible overlap when estimating the robustness region during verification. Between dissimilar classes, stricter robustness regions (i.e., larger ϵ) are enforced. If pairwise class relationships are not available initially, preferably they are generated by receiving a pre-trained classifier and then applying a clustering algorithm (e.g., agglomerative clustering) to generate them. Once pre-defined or computed pairwise relationships are available, several grouping methods are provided to create classifiers for multiple robustness criteria.
Owner:IBM CORP
Software testing method integrated with fuzzy clustering
ActiveCN112699053AImprove the efficiency of test defect detectionHelps to be killed at the same timeSoftware testing/debuggingGenetic algorithmsEngineeringMutation testing
The invention discloses a software testing method integrated with fuzzy clustering, and aims at applying a fuzzy clustering method to software testing, clustering variants simulating real defects based on similarity, and improving the software defect detection efficiency as long as similar defects are detected once. The method comprises the following steps: firstly, generating variants based on a weak variation test criterion, and calculating the similarity between the variants by adopting a mathematical statistics method; then constructing a similarity matrix, sorting the variants based on the number of the variants similar to the variants, and then fuzzy clustering the variants based on the similarity among the variants, so that non-central variants are distributed to multiple clusters, and the efficiency of generating test data is improved. The proposed fuzzy clustering method is helpful for reducing the cost of variation test , has huge potential for improving the effectiveness and practicability of variation tests.
Owner:XUZHOU UNIV OF TECH
Method for measuring dynamic characteristic similarity of complex system
PendingCN110991057ARealize real-time monitoringSolve rigid problemsCharacter and pattern recognitionDesign optimisation/simulationEarth mover's distanceAlgorithm
The invention discloses a method for measuring dynamic characteristic similarity of a complex system. A recursive analysis result has rigidity and binary value property due to the fact that a Heaviside step function is used, so an unreliable research result is produced, the slight change of a critical distance or the change of the length and the position of a time sequence can cause the obvious change of a research result; a local binary model (LBP) and a texture similarity measurement Earth Mover's Distance model (EMD) are used to propose a new idea for texture analysis of a Gaussian recursive graph for complex system dynamics characteristic analysis, and on the basis, a method system for measuring the dynamic characteristic similarity of the complex system is constructed.
Owner:HUAIHUA UNIV
Point Set Matching with Outlier Detection
Aspects of the present invention include point set matching systems and methods. In embodiments, a tree model is used to find candidate matching locations for a set of query points. In embodiments, a similitude transform is assumed, and the parameters are separately solved to reduce computation complexity. In embodiments, the dominant scaling (α) and rotation (R) parameters are obtained by identifying a maximum in an accumulator space. A translation (t) matrix is calculated in another 1D accumulator space. With the obtained similitude transform, outliers can be reliably detected. This two-stage approach reduces the complexity and calculation time of determining a similitude transform and increases the accuracy and ability to detect outliers.
Owner:SEIKO EPSON CORP
Similarity measurement method for evaluating languages based on mathematical expression
ActiveCN113051370AAvoid one-sided decision-making problemsCredible and flexible decision makingText database queryingSpecial data processing applicationsAlgorithmTheoretical computer science
The invention provides a similarity measurement method for evaluating languages based on a mathematical expression. According to the method, an interval value hesitant fuzzy language attribute set based on the mathematical expression is constructed, the preference degree relation among the attributes is found, the weight possibility probability value of each attribute is determined, the similarity between the result expression and the query expression is calculated, and finally the required mathematical expression retrieval result is displayed to a user. According to the method, starting from elements forming the mathematical expression, the interval value hesitant fuzzy language set specially used for expression query is formed by utilizing operators, operands and query keywords, so that the uncertainty and fuzziness in the formula can be expressed to the maximum extent; the problem of one-sidedness decision caused by the fact that a single determined value represents a certain object is avoided, the method is closer to the expression and description mode of people for objects, and the decision effect is more credible and flexible. The invention is subsidized by natural science fund of Hebei Province (project approval number: F2019201329).
Owner:HEBEI UNIVERSITY
Guaranteed resource similarity identification and calculation method
PendingCN111626567AImprove support capabilitiesReduce typesCharacter and pattern recognitionResourcesCosine similarityAlgorithm
The invention belongs to the technical field of use and maintenance guarantee, and relates to a guarantee resource similarity identification and calculation method. According to the guaranteed resource similarity identification and calculation method, calculation is carried out by adopting a mode of fusing a Jaccard similarity coefficient and vector space cosine similarity; and the guarantee resource similarity of the two devices are jointly expressed by a common characteristic quantity represented by a Jaccard similarity coefficient and a common characteristic numerical value represented by cosine similarity, and unified quantification operation is carried out. According to the method, a special-shaped guarantee resource similarity computer rule is established, resource similarity analysis is carried out, guarantee resources with different guarantee tasks having types and similar key characteristics are intelligently identified, and similar resource merging suggestions are given.
Owner:CHINA HELICOPTER RES & DEV INST
Class case pushing method and device based on case description
PendingCN111581353AGood effectData processing applicationsSemantic analysisAlgorithmTheoretical computer science
The invention particularly relates to a class case pushing method and device based on case description. The class case pushing method based on case description comprises the following steps: firstly,hierarchically encoding each paragraph of a decision by means of a deep learning model, forming features according to the context encoding of the paragraph, performing binary classification modeling through a multi-layer perceptron, generating a case description judgment model through training, and extracting case description of a to-be-processed decision by using the model; secondly, constructinga decision-making case description potential semantic space; and finally, mapping a query statement input by the user to a potential semantic space, calculating the similarity between the query statement and all case description vectors, sorting according to the similarity, and recommending a decision corresponding to the TopK case description to the user. According to class case pushing method and device, the influence of other types of elements except the case description is reduced, the class case pushing effect is improved, the case description can be accurately extracted from the decision, and the method and device are suitable for popularization and application.
Owner:INSPUR QILU SOFTWARE IND
Managing an installed base of artificial intelligence modules
A method (100) for managing an installed base of multiple artificial intelligence, AI, modules (2a-2d) comprising: obtaining (110), from multiple AI modules (2a-2d) and / or application domains (la- Id), pairs of input data (21) and corresponding output data (22), and / or pairs of training input data (21a) and corresponding reference data (23a), and / or configuration parameters (22a) relating to same or sufficiently similar operating situations according to a predetermined quantitative similarity criterion (3); and aggregating (120) the data (21, 23; 2 la, 23a), to form augmented training data (4) for training AI modules (2a-2d); and / or aggregating (130) the configuration parameters (22a), to form augmented configuration parameters (5) for configuring the internal processing chain (22) of AI modules (2a-2d); and / or determining (140), based at least in part on the data (21, 23), a quantitative indicator (6a-6d) for AI module (2a-2d) performance according to a predetermined quality criterion (6).
Owner:ABB (SCHWEIZ) AG
Modeling method of plant protection unmanned aerial vehicle based on assembly semantics and target recognition
ActiveCN112685837AEfficient constructionBuild accuratelyGeometric CADDesign optimisation/simulationModel extractionUncrewed vehicle
The invention discloses a modeling method of a plant protection unmanned aerial vehicle based on assembly semantics and target recognition. The method comprises the following steps: determining product part information; carrying out model establishment and processing on the determined part information by using SolidWorks; extracting names of all parts from a modeled model, carrying out semantic interpretation on the names, and determining keywords; checking the determined keywords, and checking whether the keywords belong to a semantic category or not; if the keywords belong to the semantic category, carrying out the next step; in the semantic category, determining the type of the matched part, the number of constraints and the type; the system carrying out target recognition under similarity calculation, checking whether the model is successfully matched with an example with the highest similarity, and if yes, carrying out size constraint generation and calculation; constraining the correctness of the production and resolving based on the dimensions, resulting in success of the final modeling. According to the method, a three-dimensional solid model of a plant protection unmanned aerial vehicle can be quickly, efficiently and accurately constructed.
Owner:ANHUI AGRICULTURAL UNIVERSITY
Library function identification and detection method and system based on convolutional autoencoder
ActiveCN112861131BReduce time complexityReduce space complexityBinary to binaryDecompilation/disassemblyAlgorithmTheoretical computer science
The present disclosure proposes a library function identification and detection method and system based on a convolutional autoencoder, including: extracting the instruction sequence corresponding to the binary function from each software to be tested, and then extracting the operation code in the instruction sequence; The continuous sequence of codes is counted to construct a co-occurrence matrix for each function, which is used as input to train the convolutional autoencoder model, and the convolutional autoencoder model is used to extract bottleneck features and complete model training; use training The final model encodes the library functions, and then performs similarity analysis on the library functions, and identifies the library function with the highest similarity coefficient as the final match. It has good versatility, and can directly mark various newly introduced matching objects, and obtain good results.
Owner:SHANDONG UNIV
3D model nesting and placing method based on model similarity
ActiveCN113946987ASave support materialEasy to removeAdditive manufacturing apparatusCharacter and pattern recognitionVoxelAlgorithm
Owner:ZHEJIANG FLASHFORGE 3D TECH CO LTD
Technology development stage judgment method and system based on adaptive similarity measurement
PendingCN114676752AEasy to operateHigh degree of visualizationCharacter and pattern recognitionTechnology developmentData set
The invention provides a technology development stage judgment method and system based on adaptive similarity measurement, and the method comprises the steps: segmenting an Adaner curve, and defining a plurality of technology development stages; searching technical keywords in a preset data set, generating time sequence data representing that the quantity of the science and technology data corresponding to the technical keywords changes along with time, and preprocessing the time sequence data; carrying out sub-sequence division on the preprocessed time sequence data based on a preset detail resolution, connecting all sub-sequences to generate a main sequence, and converting the main sequence into a triple form; performing similarity measurement on the main sequence and a curve representing each technology development stage through dynamic time warping; and judging the technology development stage with the highest similarity degree as the development stage of the technology. According to the method, multi-scale judgment is carried out on the technology development stage on the basis of the maturity curve and similarity measurement of the Adaner technology, and the accuracy, applicability and scientificity of judgment on the technology development stage are improved.
Owner:北京智谱华章科技有限公司
Tool feature recognition method based on deep learning
ActiveCN110472635BImprove practicalityCharacter and pattern recognitionConvolutional Deep Belief NetworksDesign plan
The invention discloses a tool feature recognition method based on deep learning, which is used to solve the technical problem of poor practicability of the existing non-standard special tool design method. The technical solution is to start with image vision, dig out the relationship between the machining features of the workpiece and the two-dimensional engineering drawing of the tool, and realize the reuse of the tool design scheme. First, based on the convolutional deep belief network generation model, the structure information and size information of the two-dimensional engineering drawing are fused, and the feature extraction of the high-dimensional tool image is performed to obtain the low-dimensional tool feature vector; then combined with the CDBN discriminant model and transfer learning, in the reuse On the basis of tool feature extraction network parameters, the relationship between processing features and tool feature vectors is mined; finally, through the two steps of tool classification based on Sofmax and similarity matching based on the cosine method of included angle, the tool feature vector to historical tool design scheme is realized. The mapping is good in practicability.
Owner:NORTHWESTERN POLYTECHNICAL UNIV
Dynamic POIs recommendation method based on TS24
ActiveCN112784162AHigh precisionImprove recallData processing applicationsDigital data information retrievalPersonalizationTime information
The invention discloses a dynamic POIs (Point of Interest) recommendation method based on TS24, and belongs to the technical field of computer application. The method comprises the following steps: 1, building a dynamic POIs recommendation architecture based on 24 time periods; 2, converting the sign-in frequency of a user into a preference value of the user for the sign-in POIs of the user by using a TF-IDF technology, and constructing a sample set theta cur in a current time period; 3, establishing a SemiDAE geographical influence model on the Tau cur; 4, according to the similarity of the sign-in behaviors of the users in the similar time periods, establishing a T-SemiDAEPOIs recommendation model with the time influence on the Tau cur; and 5, according to the two steps of pre-training and parameter fine tuning, training the T-SemiDAEPOIs recommendation model on the Tau cur. According to the method, the dynamic POIs recommendation model based on the deep learning technology is built in a novel and more reasonable mode, geographical and time information of the location social network is mined and fused, and experimental results show that the applied technology can remarkably improve the precision and recall rate of personalized POIs recommendation.
Owner:DONGBEI UNIVERSITY OF FINANCE AND ECONOMICS
A multi-instance dictionary learning and classification method and device based on similarity
ActiveCN109919165BImprove classification performanceCharacter and pattern recognitionDictionary learningClassification methods
The invention discloses a similarity-based multi-example dictionary learning and classification method, comprising: obtaining a training set; for each positive candidate example selected from a positive bag set, repeatedly performing the following steps, cyclic iteration, training a classifier, Until the preset iteration stop condition is met: calculate the similarity weights of each example in the training set for the positive class and the negative class respectively; learn each example in the training set through dictionary learning to obtain the sparse coding of each example; learn a projection dictionary, The sparse coding of each example is re-represented; based on each example re-represented by projection and the similarity weight of each example, a classifier is trained; based on the trained classifier, the category of the target package is obtained. By applying the technical solution provided by the embodiment of the present invention, the category of the target package can be accurately determined, and the classification effect of the classifier is improved. The invention also discloses a multi-instance dictionary learning and classification device based on similarity, which has corresponding technical effects.
Owner:GUANGDONG UNIV OF TECH
Multi-mode characteristic verification universal method based on dynamic time bending algorithm
PendingCN112765811AMultimodal Character DeterminationUniversalDesign optimisation/simulationMulti-objective optimisationMulti objective optimization algorithmAlgorithm
The invention discloses a multi-mode characteristic verification universal method based on a dynamic time bending algorithm, and belongs to the field of multi-mode optimization. The method takes a dynamic time bending algorithm as a theoretical support; the method specifically comprises the following steps: for a single-target problem, encoding and modeling an actual problem, then carrying out random walk sampling, calculating a dynamic time bending distance by using a sampling curve and a standard multimode test function, analyzing the similarity between the curves, and further judging the multimode characteristic of the actual problem; for a multi-target problem, after an actual problem is abstracted into a function curve, uniformly grouping a curve decision space, adopting a multi-target optimization algorithm for optimization to obtain Pareto leading edges corresponding to grouping areas, and calculating the dynamic time bending distance between multiple groups of leading edges; and analyzing the similarity between Pareto front edges of different areas, and judging the multi-mode characteristic of an actual problem in a decision space. The universal multi-mode characteristic verification method is high in universality, clear and rigorous in verification logic and good in reasonability.
Owner:BEIHANG UNIV
Artificial intelligence model transmission method and system, terminal and storage medium
ActiveCN114546258AReduce cacheReduce transmission costInput/output to record carriersEnergy efficient computingAlgorithmEngineering
The invention relates to an artificial intelligence model transmission method and system, a terminal and a storage medium. The method comprises the steps that an artificial intelligence model request is received, whether the current artificial intelligence model request belongs to a multi-model request or not is judged, and the multi-model request is the artificial intelligence model request with at least two requested target models; and if the at least two target models belong to the multi-model request, jointly judging whether the at least two target models have a packaging value by utilizing a Jaccard similarity algorithm and a frequent pattern tree algorithm, and if the at least two target models have the packaging value, packaging and transmitting the at least two target models to a model requester by adopting a packaging and transmitting mechanism. According to the application, the caching and transmission cost generated by meeting the artificial intelligence model request can be effectively reduced, so that the efficiency of the artificial intelligence application is improved.
Owner:SHENZHEN INST OF ADVANCED TECH CHINESE ACAD OF SCI +1
Method, device, equipment and medium for determining test scores based on artificial intelligence
ActiveCN112989826BAccurately determineSemantic analysisNeural architecturesMatching testFeature vector
The invention relates to semantic analysis, and provides an artificial intelligence-based method, device, equipment and medium for determining test scores. The present invention can accurately determine whether the user's answer is plagiarized through the Hamming distance of the standard vector and the user vector, and respectively analyzes the standard vector, the user vector and the test question vector through the preset encoder, and can make the test question feature vector, standard feature vector and Each element in the user feature vector integrates the contextual semantic information of the corresponding vocabulary. Through the similarity weighted operation of the standard feature vector and the user feature vector, the words with greater similarity between the user answer and the standard answer can be used in subsequent tasks. The semi-open-ended question can be accurately determined by analyzing the semantic similarity between the user's answer and the standard answer, and the matching degree between the user's answer and the test questions to be scored. In addition, the present invention also relates to blockchain technology, and the target score can be stored in the blockchain.
Owner:PING AN TECH (SHENZHEN) CO LTD
Method for judging similarity degree of any two technical systems
PendingCN112307201AReduce processingReduce distractionsCharacter and pattern recognitionCommerceAlgorithmClassification rule
The invention discloses a method for judging the similarity degree of any two technical systems, and the method comprises the steps: carrying out technical classification of technical points selectedfrom the two technical systems through a technical classification rule with a step-by-step feature, and generating two classification number sets, obtaining the number of coincident level codes in thetwo classification number sets by utilizing each level code indicated by the classification number in the two classification number sets, and further calculating the technical correlation index of the two classification number sets and the similarity probability or conflict probability of the two technical systems by utilizing the repeated number; wherein the similarity probability or conflict probability is the similarity degree of the two technical systems.
Owner:AOWEI INFORMATION TECH JIANGSU CO LTD
Program change influence analysis method based on code text and calling relationship
ActiveCN111897719AHigh precisionHigh similaritySoftware testing/debuggingEnergy efficient computingThird partyAlgorithm
The invention provides a program change influence analysis method based on a code text and a calling relationship, which belongs to the field of software engineering and comprises the following steps:1, acquiring a method calling relationship of each method through third-party software; step 2, analyzing method text similarity of the initial change set and other method sets from the perspective of the code text; 3, analyzing the method call correlation of the initial change set and other method sets from the perspective of the method call relationship; and 4, calculating a comprehensive method dependence degree according to the method text similarity and the method calling correlation between the initial change set obtained in the step 2 and the method text similarity and the method calling correlation between the initial change set obtained in the step 3 and each method set, thereby obtaining a predicted affected method set. Compared with an existing word differentiation technology for experiment, the method provided by the invention has certain advantages in accuracy.
Owner:毛澄映 +2
Optimized code decompiling method and system based on deep learning
PendingCN114691151AImprove accuracyImprove readabilityDecompilation/disassemblyProgram documentationData setAlgorithm
The invention relates to an optimized code decompiling method and system based on deep learning. The method comprises the following steps: acquiring a low-level intermediate language LIR and a high-level intermediate language HIR by utilizing a low-level programming language LPL and a high-level programming language HPL to serve as a training data set; training a deep learning model by using the training data set, learning a mapping rule between the LIR and the HIR, and translating the LIR of the LPL to be decompiled into the HIR by using the trained deep learning model; performing data stream recovery and control structure recovery on the HIR obtained by the deep learning model to generate an HPL code; and searching an active code similar to the generated HPL code by utilizing a similarity matching algorithm, and migrating semantic information in the active code into the generated HPL code. According to the method, the LPL can be automatically converted into the HPL, and high accuracy is achieved for optimized and unoptimized binary decompilation.
Owner:INST OF INFORMATION ENG CAS
Source code comparison method and system oriented to technical features and program product
ActiveCN114880023AEfficient extractionPreserve logic call informationReverse engineeringEnergy efficient computingSemantic vectorAlgorithm
The invention discloses a technical feature-oriented source code comparison method and system and a program product, and belongs to the technical field of natural language processing. The method comprises the steps that a semantic coding method based on a function call structure is used, and code similarity is analyzed from the aspects of the function call structure, a function name, a built-in class and the like; carrying out graph semantic encoding by adopting an auto-encoder method based on a graph convolutional neural network, and comparing code structure semantics based on semantic vectors; based on the calling information vectors of the functions and the built-in class names, comparing the similarity of the functions with the similarity of the built-in classes; and finally, splicing the structure vector, the function vector and the built-in class vector as an overall technical feature vector, and comparing the code similarity. According to the method, technical feature information such as function names, calling structures and built-in classes is comprehensively considered, and code comparison can be better carried out according to technical features.
Owner:SHANDONG UNIV
Method and device for quantifying thinking similarity of testers
PendingCN114385482AClarify test technique differencesImprovement of thinking abilityCharacter and pattern recognitionSoftware testing/debuggingTest efficiencyAlgorithm
The invention discloses a method and a device for quantifying thinking similarity of testers, and the method comprises the steps: classifying the first-round defects measured by the testers in the first round, and calculating the defect degree coefficient of the classified first-round defects; calculating an initial test thinking classification metric value of each tester under the corresponding test thinking category; calculating a corrected test thinking classification metric value of each tester under the corresponding test thinking category; calculating a test thinking classification metric value of each tester under the corresponding test thinking category, and calculating a standardized test thinking classification metric value of each tester under the corresponding test thinking category; and calculating a test thinking similarity value among the testers. According to the method, the test technology difference of the testers can be effectively determined, so that the problems of thinking ability improvement of the testers, team combination of different testers, test team cultivation and the like are effectively solved, and the effects of improving the project defect discovery probability and the test efficiency are achieved.
Owner:电信科学技术第十研究所有限公司
Software Local Plagiarism Detection Method Based on Birthmark of Dynamic Instruction Dependency Graph
ActiveCN108399321BNot easy to confuse and destroyImproved ability to combat deep obfuscationProgram/content distribution protectionAlgorithmTheoretical computer science
The present invention proposes a software partial plagiarism detection method based on dynamic instruction dependency graph birthmark, including: 1) using dynamic instrumentation to monitor the program at the instruction level to capture the instruction track of each function; 2) recording each function’s dynamic instruction trajectory, carry out data dependency and control dependency analysis, and construct a dynamic instruction dependency graph birthmark; 3) calculate the similarity between instruction dependency graph birthmarks, and realize the measurement of similarity between functions; 4) based on a given threshold, for the plaintiff Each function in the program builds a suspicious function table; 5) Extract the static function call graph of the program, and under the guidance of the call dependency, perform accurate one-to-one pairing of suspicious functions; 6) Based on the call dependency, assemble the matching function pair to generate Plagiarism evidence map, measuring the proportion of suspected plagiarism. The invention realizes the detection of partial plagiarism by constructing function-level birthmarks; the invention proposes the concept of plagiarism evidence map for the first time, which can greatly enhance the effectiveness of evidence.
Owner:XIAN UNIV OF POSTS & TELECOMM
Designer role management and control method
InactiveCN111325454AImprove execution efficiencyFix execution time issuesResourcesComplex mathematical operationsSimilarity theoryRole management
The invention provides a designer role management and control method, and relates to the technical field of computer-aided management of designers. The method comprises the following steps: step 1, calculating the similarity of design tasks, including design file similarity, design model similarity and design task aggregation similarity; when a design task is executed, establishing a design modelas a basis, and actually editing a design file on the basis of establishing the design model, so that calculation of design task aggregation similarity is divided into calculation of design file similarity and design model similarity, 2, establishing a learning efficiency model based on the design task aggregation similarity, and calculating a learning efficiency curve executed by a designer task;3, considering the similarity degree between the design tasks, combining the learning effect of the designer with the similarity theory, and predicting the execution time of the design tasks; and 4,performing designer role allocation on the basis of considering the learning ability of the designers and the similarity between the design tasks.
Owner:GUANGZHOU METRO DESIGN & RES INST
Text similarity measurement method and device based on multi-model fusion
ActiveCN112784587APrevent overfittingReduce difficultyNatural language translationSemantic analysisAlgorithmSimilitude
The invention provides a text similarity measurement method based on multi-model fusion. The method comprises the following steps: preparing a training set and a test set; selecting four deep learning training models: Bert, Paddle, Xlnet and Tree-LSTM; for each training model, acquiring C sub-models; for each sub-model, calculating a similarity score and a loss function of the input data; evaluating the sub-models; selecting and fixing a group of super-parameter combination with the best evaluation value of each sub-model; continuously training each sub-model to converge a loss function, and storing the 4C sub-models at the moment; fusing the 4C sub-models by adopting a Boosting scheme so as to perform weighted addition on similarity scores of the sub-models to obtain a similarity measurement model; and testing and adjusting the similarity measurement model by using the data of the test set. According to the method, the accuracy of similarity measurement is effectively improved, the recall rate and accuracy of similarity judgment are improved, and the generalization ability of the model is improved.
Owner:QUANZHOU POWER SUPPLY COMPANY OF STATE GRID FUJIAN ELECTRIC POWER +2
A 3D model nesting placement method based on model similarity
ActiveCN113946987BSave support materialEasy to removeAdditive manufacturing apparatusCharacter and pattern recognitionVoxelAlgorithm
Owner:ZHEJIANG FLASHFORGE 3D TECH CO LTD
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