8 results about "Reference software" patented technology

The invention provides a website detection method and device and electronic equipment, and relates to the technical field of artificial intelligence, in particular to the technical fields of artificial intelligence, intelligent search, large models and the like. According to the specific implementation scheme, a software library is determined, the software library comprises reference software with software downloading data larger than set software downloading data, combination is carried out according to the reference software and set search terms, at least one to-be-detected sample is determined, and the to-be-detected sample at least comprises a to-be-detected website; according to the to-be-detected sample, obtaining a reference example sample during large model reasoning; a detection result of the to-be-detected sample is determined through a large model according to the to-be-detected sample and the example sample, and the detection result is used for indicating whether the to-be-detected website is a counterfeit website or not.

The invention discloses a system deployment method and device and a storage medium. The method comprises the following steps: determining a target system to be deployed and a target server to which the target system is to be deployed; benchmark information of a benchmark server is obtained, a target system is deployed on the benchmark server, and the benchmark information comprises benchmark software and hardware information and benchmark configuration information; target information of a target server is obtained, and the target information comprises target software and hardware information; determining target configuration information of the target server according to the reference software and hardware information, the reference configuration information and the target software and hardware information; and deploying the target system on the target server according to the target configuration information. Through the method and the device, the problem that the deployment efficiency of the target system is low due to the fact that the number of the working processes which should be started when the target system is deployed on the target server depends on manual adjustment in the related technology is solved.

The invention belongs to the technical field of computer software engineering, and relates to a software demand intelligent analysis and prediction method and system, and the method comprises the following steps: obtaining a user operation log of target software, and constructing dynamic task chain data reflecting the actual process of a user based on a continuous operation sequence in the user operation log; associating a behavior pattern recorded in the dynamic task chain data with a feedback text submitted by a user, performing cross validation on the feedback text, and generating a credibility score representing the authenticity of the feedback text; the potential demand value is evaluated by combining high-credibility feedback and dynamic task chain data screened out through credibility scoring; performing constraint optimization according to preset development resource evaluation data to obtain a function combination after constraint optimization; according to the method, the problem that when the reference software and the target software have a large difference in function positioning or user groups, the built function model can generate dislocation, and large deviation occurs in analysis of user behaviors is solved.

This paper proposes a low-complexity, hardware-friendly technique for video decoding systems to mitigate striping artifacts while maintaining compression efficiency. Generally, the proposed technique consists of two stages: a striping detection stage and a destripping stage. The striping detection stage identifies potential striping artifact regions in the image / video based on gradient information and other data. The destripping stage applies correction techniques to these identified regions. In one implementation, the destripping modifies the filtering logic proposed by previous video decoding standards for other filtering applications to mitigate striping. When implemented on the AVI video decoding standard and the AOM Video Model (AVM) reference software, the proposed technique significantly improves subjective quality at a reasonable hardware implementation cost. The methods and implementations presented in this document can be beneficially applied to various image / video decoding standards and systems.

The invention provides a software asset analysis method and device, electronic equipment, a medium and a program product, and can be applied to the technical field of big data and the technical field of artificial intelligence. The method comprises the steps of obtaining a target event; determining at least one target analysis dimension and a corresponding affected data range based on the target event and preset event rule information; according to the affected data range, incremental updating is conducted on a dynamic topological graph, an updated topological graph is obtained, and the dynamic topological graph represents the relation between software assets and corresponding associated entities; performing incremental aggregation calculation on the reference software asset analysis result of the target analysis dimension based on the updated topological graph to obtain an updated software asset analysis result; and generating a software asset analysis result for target software based on the updated software asset analysis result.

The application discloses an OPC software verification method, an OPC software verification device, an electronic device and a storage medium. The method comprises the following steps: obtaining first data, wherein the first data comprises data for establishing an OPC model and a test layout; obtaining reference data and a reference correction program corresponding to reference OPC software and verification data and a verification correction program corresponding to to-be-verified OPC software according to the first data, the reference OPC software and the to-be-verified OPC software; and evaluating a verification result of the to-be-verified OPC software according to the reference data and the reference correction program, the verification data and the verification correction program and a preset evaluation threshold. The application introduces the reference OPC software as a verification standard for verifying the to-be-verified OPC software, so that actual feature sizes can be collected without actual exposure of a photomask when the OPC software is verified, and the verification cost can be effectively reduced. Meanwhile, the OPC software can be verified in advance when the OPC software is verified, and the verification time can be greatly reduced.

This invention discloses a dynamic user profile update method based on multimodal data, relating to the field of user modeling technology. The method includes: acquiring the collaborative analysis software of each software in the user's device; obtaining the association weight based on the association filtering value of the collaborative analysis software; acquiring status update words and updating the user's profile based on the collaborative analysis software of the updated reference software and the association weight of the collaborative analysis software. This invention addresses the problem in existing dynamic user profile update methods that lack analysis of multimodal data generated by users based on user software usage data. This results in the inability to effectively acquire dynamic profile data related to the user's immediate interests and needs, leading to inaccurate user profiles and a loss of dynamism after data processing.

The application discloses a software defect repair information determination method and device and electronic equipment, and is applied to the fields of artificial intelligence technology and intelligent automobile technology. The method comprises the following steps: obtaining software defect information, wherein the software defect information comprises an error log and software defect code information corresponding to the error log; screening reference software defect repair information related to the software defect information from a software defect repair information set according to the similarity value of the error log and each software defect repair information in the software defect repair information set; and determining defect repair information for the software defect code information according to the similarity value of the error log and the reference software defect repair information and the reference software defect repair information. The method screens the reference software defect repair information based on the similarity, and generates adaptive defect repair information accordingly, thereby reducing the dependence on manual work and improving the accuracy of software defect repair.