57 results about "Case identification" patented technology

A landmark case identification system and method in which the user is presented with a set of the most relevant documents on a selected topic. This set, which is dynamic and asserted to be inclusive at any point in time, is presented to the user in a Virtual Digest and initially sorted by court / date order. The user has an option to resort the answer set using a Frequently Cited sort option, which causes the system to dynamically analyze the answer set for references between the documents. Landmark cases are identified by their peers in the domain as they will be referenced and relied upon most often. The user is presented with the resorted answer set, and information detailing how many other cases in the domain referenced them is now included.

The invention relates to a software error positioning method and device. The method comprises the steps that through a source code of a testing case driving program, execution path information and a corresponding execution result of the program are acquired, wherein a successful execution path and a failure execution path are involved; an NJW spectral clustering algorithm is adopted for conductingclustering division on the execution path information of the program, an accidental correctness testing case is identified, and the identified accidental correctness testing case is removed; the suspicious degrees of codes are calculated, and a highly-suspicious code of which the suspicious degree is higher than a set suspicious degree threshold value is acquired; an association code associated with the highly-suspicious code is mined on the failure execution path; with the mined association code as a code inspection object, software error positioning is conducted. The software error positioning method has low false report rate and missing report rate on accidental correctness testing case identification, the accuracy rate of software error positioning is increased, and the efficiency ofsoftware error positioning is improved.

The invention discloses a serial / incorporated case identification method and system. The method comprises the following steps of carrying out preprocessing: carrying out word segmentation and part-of-speech tagging on the case detail description of a case, and removing stop words; extracting the important characteristics of the case from the preprocessed case detail description through a method which combines a rule with a dictionary, and converting a case text into a characteristic vector; and according to the characteristic vector, adopting a case characteristic similarity calculation method to obtain the comprehensive similarity of the cases, clustering the cases through the comprehensive similarity, and finding the dense cluster of related cases to identify the serial / incorporated cases. Through the method and the system provided by the invention, clustering is carried out on the basis of characteristic density, and limitation that a traditional clustering algorithm is applied to a numeric type vector is eliminated. A difficult point that possible serial / incorporated case clusters cannot be obtained from a case detail text library is overcome. The method and the system can be applied to case investigation to improve investigation efficiency.

The invention relates to big data, and provides an abnormal case identification method based on artificial intelligence which is applied to a platform server. The method comprises the steps: acquiringdiagnosis and treatment project data corresponding to the same disease, taking diagnosis and treatment time as a unit, and taking the diagnosis and treatment project data as words in a text to conduct text construction, wherein the constructed text comprises the diagnosis and treatment project data of different users of the same disease in the corresponding diagnosis and treatment time period; performing topic model construction on the text to obtain corresponding topic vector distribution, wherein each topic vector distribution is corresponding to one topic and comprises a plurality of wordidentifiers and corresponding word weights, and the topics have different user topic weights for different users; aligning the topic vector distribution corresponding to each text and performing clustering to obtain diagnosis and treatment item categories corresponding to each user at different time to form a diagnosis and treatment sequence corresponding to the user; and inputting the diagnosis and treatment sequence corresponding to each user at different diagnosis and treatment time into the process mining model to obtain a standard clinical path corresponding to the disease type so as to identify the abnormal case.

The invention relates to an automated software test, which discloses an automated test method and device, an apparatus and a storage medium. The method comprises the following steps: receiving an automated test request and reading an incoming parameter data contained in the automated test request; Searching the corresponding outgoing data and case identification of the input parameter data in thepreset spreadsheet; Finding the corresponding target test cases in the test case database according to the case identification, and executing the target test cases to obtain the case execution results; Matching the data of the outgoing parameter data according to the result of the case execution, and obtain the matching result since the invention searches the corresponding outgoing data in the pre-configured spreadsheet according to the obtained incoming parameter data, Then, according to the data of the test case, the data of the test case is matched, so that the parameter data can be obtained from the external system without the operation of opening the wall and the parameter matching is carried out, which ensures the smooth progress of the automated test and also improves the test efficiency.

The invention discloses a legal case similarity discrimination and pushing method, and the related discrimination method comprises the steps: carrying out the classification of a target legal case, and extracting historical cases of the same type from a historical case database according to the obtained case types to form a candidate set; performing event sequence representation on the target legal case and each similar historical case in the candidate set; according to the event sequence measurement model, calculating the distance between the event sequence corresponding to the target legal case and the event sequence corresponding to each historical case in the candidate set; and based on the distance of the event sequence and in combination with a scoring function, calculating the similarity between the target legal case and historical cases in the candidate set. According to the method, more comprehensive and accurate class case identification can be realized; meanwhile, the legalinstrument is expressed as a time sequence event sequence, similarity calculation is carried out on the basis of an unsupervised mode, historical cases with high scores are selected for pushing, manpower input is greatly reduced, and pushing intelligence can be better achieved.

The invention provides a cloud film reading method, an integrated display terminal and a computer storage medium. The cloud film reading method is applied to the integrated display terminal and comprises the following steps of acquiring a trigger signal, wherein the trigger signal comprises case identification information; acquiring an image from a server according to the case identification information and displaying the image on a screen. Through the cloud film reading method, the integrated display terminal can acquire and display the film reading information from the server.

The invention provides a method and device for storing and taking articles on the basis of face recognition. The method comprises the steps that face features of a user are collected through a camera;whether current face features exit in a face data list or not is judged, wherein the face data list comprises face features of at least one user; if the current face features exist in the face data list, one case of a locker is opened randomly, after the user stores the articles, first case closing information is received, case identification of the case and the face features of the user are correspondingly saved in a storage list, and then it is determined that the user stores the articles at present. The process that the user carries around bar code paper, a card, a key and the like after depositing the articles is not needed; the user can store the articles by means of the face recognition method, the user can store and take the articles conveniently, unnecessary troubles brought by misoperation of the user are effectively avoided, and the user can free hands thoroughly.

The invention relates to a sentence meaning composition relation lamination identification method based on central blocks, and belongs to the technical field of computer science and Chinese information processing. The sentence meaning composition relation lamination identification method based on the central blocks is based on contemporary Chinese language semantics, and solves the problem of Chinese sentence meaning composition relation identification in a Chinese sentence meaning structural model. The sentence meaning composition relation lamination identification method based on the central blocks gives a concept of 'layer central block' firstly, and achieves effective mapping from a syntactic structure to a sentence meaning structure. A sentence meaning composition relations identification problem is divided into three layer relation identification problems, namely a relation between predicates, a relation between basic case and the predicates, and a relation between general case and sentence meaning compositions. Central block identification algorithm, basic case identification algorithm, general case identification algorithm, identification algorithm of the relation between the predicates, identification algorithm of the relation between the basic case and the predicates, identification algorithm of the relation between the general case and the sentence meaning compositions are respectively provided. A computer can analyze and acquire the sentence meaning composition relation in high accuracy rate and efficiency, and study of the Chinese sentence meaning structural model is further promoted.

The invention aims to provide a method and equipment for providing information. The method comprises the following steps: receiving a data query request sent by user equipment; in response to the data query request, analyzing the one or more pieces of field information to obtain one or more pieces of condition field information and inter-condition relationship field information in the one or more pieces of field information; determining one or more corresponding candidate target case identification information sets according to the one or more pieces of condition field information; and performing set operation on the one or more candidate target case identification information sets according to the one or more inter-condition relationship field information to generate one or more pieces of target case identification information. The retrieval efficiency can be improved, and the condition query complexity can be reduced.

The invention provides a business processing method and device, and the method comprises the steps: receiving a project case processing request of a user, and enabling the project case processing request to carry project target case identification information and the identity identification information of the user; obtaining project target case details pre-stored in a database according to the project target case identification information, and creating a credit agreement order based on the project target case details and the identity identification information of the user; obtaining performance data information of the credit agreement order within a preset duration; and adjusting the credit evaluation of the user according to the performance data information.

The invention relates to a non-motor vehicle riding-walking traffic accident identification method. The method comprises steps that 1, traffic accident site survey is carried out, damage conditions of relevant detected objects are comprehensively acquired and recorded; 2, survey data is analyzed by experts, and an identification conclusion is determined by the experts; 3, non-motor vehicle riding / walking traffic accident identification data is written in; 4, the gathered data is introduced into a statistics analysis software SPSS statistics, attributes including variable names, variable types, variable labels, default values, code numbers and the code position are defined, data cleaning preprocessing is accomplished, and a non-motor vehicle riding-walking traffic accident identification information database is finally established; 5, analysis on correlation between the survey variables and the identification conclusion is developed; 6, a non-motor vehicle riding / walking identification discriminant analysis model is constructed; and 7, a to-be-determined case identification conclusion is determined. The method is advantaged in that judicial expertise work efficiency is effectively improved, and identification accuracy is improved.

The invention discloses a non-vehicle insurance assessment remote online video survey system. The system comprises a case structured information processing subsystem, a case online remote video acquisition subsystem and a system user. The system user uses a smart phone or a computer to perform data interaction with the case structured information processing subsystem and the case online remote video acquisition subsystem through a Unicom network, a telecommunication network or a mobile network so as to realize insurance assessment remote online video survey. According to the non-vehicle insurance assessment remote online video survey system, rapid acquisition of insurance case field information and online case identification are realized, and online loss assessment and claim settlement byassessors are facilitated. The client role is converted into the on-site assessor, the scheduling pressure of the assessor is released, and the client does not need to wait for the survey personnel inplace, so that the client experience and satisfaction are improved, and a large amount of on-site survey labor cost is saved.

Speech keywords are extracted from voice data on a response that an operator has made to an inquiry from a customer while referring to case data. Response keywords to be responded to the inquiry are extracted from the case data. After detecting a common keyword in the speech and response keywords, a support keyword is extracted from the speech keywords that appears in the response at a time near the appearance of the common keyword and that does not match the response keywords. Auxiliary data is stored which includes case identification information uniquely identifying the case data, a customer level indicating a knowledge level of the customer about the inquiry, and the support keyword.

The invention discloses an abnormal case identification method and device based on a tree structure, equipment and a storage medium, and belongs to the technical field of artificial intelligence, andthe method comprises the steps: obtaining an original training sample from an initial case database; calculating an abnormal score of the original training sample based on an IForest algorithm; comparing the abnormal score of the original training sample with a preset threshold, classifying the original training sample according to a comparison result, and forming a target training set; performingmodel training on the initial recognition model through the target training set, and outputting an abnormal recognition model; and importing the case data of the to-be-identified case into the exception identification model, and outputting an identification result. The invention also relates to a blockchain technology. The abnormal score of the original training sample can be stored in the blockchain. The abnormal score of the original training sample is calculated based on the IForest algorithm, and the original training sample is classified according to the abnormal score so that the interference of human factors is effectively eliminated, and the accuracy of the case abnormality recognition model is improved.

The embodiment of the invention discloses an abnormal case identification method based on data analysis and a computing device. The method includes the following steps: the computing device receives case data of a first case, the case data includes actual medical insurance cost; Finding a first basic disease score corresponding to a first disease classification to which the first case belongs in adisease score dictionary table, and calculating a predicted medical insurance expense of the first case according to the first basic disease score, wherein the disease score dictionary table comprises a corresponding relationship between the disease classification and the basic disease score; Further, it is judged whether the first case is an abnormal case according to the actual medical insurance cost and the predicted medical insurance cost, and if so, prompting information for prompting the first case to be abnormal is outputted, and by performing the above method, it is possible to realize the identification of the abnormal case.

The invention discloses a non-vehicle insurance public estimation remote online video survey system and method, and the system comprises a case structured information processing subsystem, a case online remote video collection subsystem, and a system user. The system user uses a smart phone or a computer to perform data interaction with the case structured information processing subsystem and thecase online remote video collection subsystem through a Unicom network, a telecommunication network or a mobile network so as to realize insurance public estimation remote online video survey. According to the non-vehicle insurance public estimation remote online video survey system and method, rapid acquisition of insurance case field information and online case identification are realized, and online loss assessment and claim settlement by public estimators are facilitated. The client role is converted into the on-site public estimation personnel, the scheduling pressure of the public estimation personnel is released, and the client does not need to wait for the survey personnel in place, so that the client experience and satisfaction are improved, and a large amount of on-site survey labor cost is saved.

The embodiment of the invention provides a survey task allocation method and device, electronic equipment and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring original case data and business data; performing case simulation analysis according to the original case data and the business data to obtain preliminary survey data; performing identification processing on a target case in a preset area through the preliminary survey data and a preset case identification model to obtain target survey data of the target case and case processing data of the target case; performing data analysis on the target survey data and the case processing data through a pre-trained data analysis model to obtain a prediction survey index; according to the prediction survey index and the reference survey index, performing measurement and calculation processing on the target survey data to obtain survey manpower data; and distributing survey tasks according to the survey manpower data. According to the embodiment of the invention, the accuracy of survey task dispatching can be improved.

The invention discloses a high-fraud-risk case identification method and apparatus, and a computer device, relates to the technical field of information, and mainly aims to improve the identification precision of high-fraud-risk cases. The method comprises the steps of obtaining attribute information corresponding to a to-be-identified case, wherein the attribute information comprises time information and position information; inputting each piece of attribute information into a preset spatial-temporal feature extraction model for feature extraction to obtain a spatial-temporal feature vector corresponding to the to-be-identified case; calculating the similarity between the to-be-identified case and a first sample high-fraud-risk case based on the spatial-temporal feature vector corresponding to the to-be-identified case and the spatial-temporal feature vector corresponding to the first sample high-fraud-risk case; and judging whether the to-be-identified case is a high-fraud risk case or not according to the calculated similarity. The method is suitable for identifying high-fraud risk cases.

Speech keywords are extracted from voice data on a response that an operator has made to an inquiry from a customer while referring to case data. Response keywords to be responded to the inquiry are extracted from the case data. After detecting a common keyword in the speech and response keywords, a support keyword is extracted from the speech keywords that appears in the response at a time near the appearance of the common keyword and that does not match the response keywords. Auxiliary data is stored which includes case identification information uniquely identifying the case data, a customer level indicating a knowledge level of the customer about the inquiry, and the support keyword.

The embodiment of the invention discloses a batch risk case identification method and device and an electronic device. The method comprises: acquiring original event data corresponding to multiple risk cases; processing the original event data of the plurality of risk cases to obtain target event data of the plurality of risk cases, the target event data comprising a preset variable for describingcommitting features; clustering the target event data of the plurality of risk cases based on a density clustering algorithm to obtain clustering results of the plurality of risk cases; and identifying batch risk cases based on the clustering result.

The invention relates to the field of artificial intelligence, and discloses a fraudulent case identification model training method and device and computer equipment, which can more accurately identify fraudulent cases which are not marked in historical claim settlement cases under the condition of fewer fraudulent samples so as to increase the number of positive samples, and have the effect of filtering dirty data at the same time, the condition that samples in an original data set are unbalanced is improved, and then the fraudulent case classifier is constructed through the obtained data set, so that the classification accuracy of the obtained fraudulent case classifier is higher.

The invention relates to an arbitrary strength combined test case generation method, which comprises the following steps of: 1, generating a combined test case complete set; 2, mapping a use case identification vector; 3, selecting test cases, setting an initial cumulative vector as a zero vector, calculating the weight and dispersion of each test case, performing weighting to obtain a target function value, obtaining the test case with the maximum target function value, adding an identification vector corresponding to the case into the cumulative vector, wherein the calculation of the weightand the dispersion depends on the bit operation between the identification vectors; and 4, judging whether the coverage table meets the coverage requirement or not through the accumulation vector, ifso, screening out the minimum coverage table by adjusting the weights of the weight and the dispersion, otherwise, returning to the step 3, and continuing to select the test cases. According to the invention, the generation of the minimum coverage table of any intensity can be realized.

The invention discloses a one-case-one-code information transmission, verification and management method. The method comprises the steps of issuing judicial information, submitting the judicial information, allocating the judicial information, generating a case identification code and generating a case two-dimensional code. Firstly, judicial information is issued, enters a one-case one-code information transmission, management and verification platform; the one-case one-code information transmission, management and verification platform allocates judicial information to the case coding area, the case fingerprint area and the case index area; a serial number, a verification code, a case index and a case identification code are generated in a case coding area, a case fingerprint area and a case index area, the serial number, the verification code and the case index are combined through the method to generate the case identification code, and the case identification code generates a casetwo-dimensional code through a two-dimensional code generation algorithm. The one-case-one-code information transmission, verification and management method has the advantages that consulting is moreconvenient and accurate, the storage cost is low, the safety is high, and consulting traces are left.

The invention discloses a sensitive case identification method and device. The sensitive case identification method comprises the steps of obtaining case information of a target case; performing key information matching processing on the case information and preset sensitive case feature information, and identifying whether the target case is a sensitive case or not according to a matching result,wherein the sensitive case feature information comprises stability-related case information, hot topic information of a preset media platform and sensitive party information. By adopting the technical scheme, whether the case is a sensitive case or not can be automatically judged according to the case information, the technical scheme is applied to a sensitive case identification scene, the laborcost can be reduced, and the sensitive case identification efficiency is improved.

The invention relates to interface testing equipment for testing by an interface testing method. The testing equipment is electrically connected with a power supply device and comprises a testing instruction acquisition module, a precondition query module, a parameter information acquisition module, a use case module acquisition module and a test case generation module, wherein the test case generation module is used for generating a test case for an interface to be tested and a test module for the interface to be tested according to the parameter information of the use case to be tested and atemplate of the use case to be tested; the parameter information acquisition module comprises a pre-information query module, a pre-use case generation module and a use case parameter acquisition module; and the power supply device comprises a solar battery and a 220V mains supply, wherein the solar battery and the 220V mains supply independently work, and the solar battery and the 220V mains supply are automatically switched through a photoinduction module and a solar battery electric quantity detection module. By use of the equipment, test use case identification and precondition conditioninformation are associated, the test efficiency of automated testing is improved, and in addition, the working stability of the device is improved.

The invention relates to a data processing method and device. The method comprises the following steps: acquiring case identification information corresponding to a target service scene; sending a usecase protocol request to a use case server, the use case protocol request including the use case identification information, and the use case server storing use case protocol data corresponding to aplurality of service scenarios; receiving case protocol data corresponding to the target service scene; and processing an interaction event in the target business scene based on the use case protocoldata. By utilizing the data processing method and device provided by each embodiment of the invention, the client does not depend on the business server in the test process, and unnecessary business risks caused by modifying development codes and deployment modes of the business server can be avoided.

The invention discloses a method based on the automatic log of a collection system, a storage medium and an application server. The method comprises the following steps of when a browser is detected to be started, detecting whether a starting mode of the browser is a preset starting mode, wherein the preset starting mode is to start the browser at a debtor information interface; when the startingmode of the browser is a preset starting mode, collecting the search information contained in a search web page displayed by the browser, and generating a first work log according to the search information; associating the first work log with a first case identification corresponding to the debtor information interface and storing the first work log. The invention forms a specific working log withthe debtor information of the collection system through the network searching record and the recording text record, so as to solve the problems encountered in the work and play the roles of reminding, tracing and proving in the follow-up.

The invention discloses a method for signing for a case, and terminal equipment. The method comprises the following steps that: according to case information in advance, setting a case identificationcode for the case; and through the terminal equipment, scanning the case identification code corresponding to the case to finish signing for the case. By use of the method, the case identification code is set for the case in advance, so that the case identification code can be scanned through the terminal equipment to finish signing for the case. Compared with a traditional pen and paper signing-for way, the way obviously greatly improves efficiency, and in addition, specific signing-for time can be obtained so as to bring convenience in traceability; and through the case identification code,the case can be more easily searched, and management is convenient.