18 results about "Result list" patented technology

Disclosed are a method and device for communication using a fronthaul interface. An operation method of an O-RU includes the steps of: generating a plurality of first measurement results by performing measurement operations on a first measurement target in a single notification period according to a notification interval; generating a first measurement result list including the plurality of first measurement results; and transmitting, to an O-DU, a message including the first measurement result list.

The application discloses an automatic high-division meter selecting method and system based on a heterogeneous platform, relates to the technical field of electric energy meter detection, and has the following advantages: in the task configuration stage, a user can conveniently check and select verification items and set related parameters through a graphical interface; in the instruction conversion and issuing stage, the configured task can be parsed into standardized control instructions and converted into special communication messages recognizable by the heterogeneous platform; in the verification execution and data collection stage, key data can be collected in real time and verification states can be dynamically displayed; in the automatic fine adjustment and rechecking stage, fine adjustment operations are automatically performed according to error data and rechecking is circularly performed; in the intelligent scoring and ranking stage, a comprehensive score is calculated and ranked by adopting a differentiated scoring rule and combining a weight coefficient; and in the result output stage, a detailed verification report can be generated and a meter selecting result list can be output, so that the adaptation of the heterogeneous platform, data processing and process control are realized.

The application discloses a content recommendation scene-based experiment strategy evaluation method, device and medium, comprising: creating opposite first and second shunt paths for first and second virtual recommendation requests; generating a first recommendation combination strategy based on N recommendation strategies associated with N path nodes in the first shunt path, and generating a second recommendation combination strategy based on N strategies associated with N path nodes in the second shunt path; obtaining a first recommendation result list by processing the first virtual recommendation request based on the first recommendation combination strategy, and obtaining a second recommendation result list by processing the second virtual recommendation request based on the second recommendation combination strategy; obtaining a target recommendation result list by combining the first and second recommendation result lists; and evaluating the effect difference of different recommendation strategies based on user feedback data of the target recommendation result list. The application can improve the AB test accuracy in the content recommendation scene.

The application discloses an open source platform task matching method based on a developer behavior graph and double-layer filtering, and the method comprises the following steps: S1, dividing the behavior characteristics of the developer into three dimensions to obtain a developer behavior characteristic data set; S2, identifying and screening out developers who do not meet the basic requirements; S3, constructing a lightweight knowledge graph G containing the nodes of the developers, the nodes of the tasks and the associated edges of the nodes by combining a relational database with a graph storage dev_task ; S4, obtaining the task requirement text Text req of the historical open source task and the open source task to be matched, obtaining a plurality of subtasks by decomposing the requirement of the open source task to be matched, and generating corresponding vectorized representations; S5, adopting a double-layer filtering strategy, constructing a primary matching layer to obtain a preliminary candidate developer set, and constructing a fine screening scoring layer to obtain a recommended result list.

This invention discloses a RAG question-answering optimization method and system based on fusion retrieval, relating to the field of large-scale model knowledge question-answering technology. The method includes acquiring user queries, performing keyword retrieval and semantic vector retrieval in parallel, obtaining keyword retrieval result lists and semantic vector retrieval result lists respectively. Based on multi-dimensional quality assessment, the quality score of each text unit in each retrieval result list is calculated, and text units with quality scores below a preset quality threshold are filtered out. A quality-weighted inverse ranking fusion algorithm is used to sort the text units in all filtered retrieval result lists. Based on the length of each text unit and its document format, contextual content enhancement and merging are performed on the sorted text units to generate an enhanced context block list. Based on the enhanced context block list and the user query, structured prompt information is constructed, and the structured prompt words are input into the large language model to generate and output the final answer.

The application relates to an artificial intelligence-based homogeneous API recommendation method and device, electronic equipment and a storage medium. The method comprises the following steps: obtaining a homogeneous API set containing candidate APIs corresponding to a business request according to a business request submitted by a user; obtaining a request quantity prediction value of each candidate API in the homogeneous API set; obtaining running state information of each candidate API in the homogeneous API set; obtaining a basic score of each candidate API in the homogeneous API set, and updating the score of each candidate API based on the request quantity prediction value and the running state information of each candidate API to obtain a latest score result list of each candidate API; and determining a target API matched with the business request recommended to the user according to the latest score result list of each candidate API. The scheme provided by the application can realize timely, automatic and standardized API recommendation, improve the overall resource utilization rate, and meet the demand of AI capability calling of the user.

This application relates to the field of search optimization technology, specifically to a search optimization method and system for a procurement platform based on intelligent recommendation algorithms. The method includes: evaluating the consistency of user behavior between two search terms; calculating the behavioral correlation between any two search terms; mining search terms that are synonymous with the current user's search terms; constructing a search extension set; and selecting products whose product information contains search terms from the search extension set as candidate products; determining the matching coefficient for each candidate product; determining the semantic correlation and correlation coefficient between any two products based on all users' historical purchase records; and determining the priority recommendation value for each candidate product based on the correlation coefficients between different products and each candidate product in the current user's historical purchase records, combined with the matching coefficients, thereby generating a recommendation result list for intelligent recommendation and display. This application significantly improves user search efficiency, procurement experience, and platform cross-selling conversion rate.

This invention provides a vulnerability patch sorting method based on decomposition analysis and progressive comparison. The method includes the following steps: For each candidate submission, a structured decomposition analysis report containing vulnerability-related and irrelevant changes is generated using a large language model; using this report and historical remediation cases, each candidate submission is binary-classified, with submissions classified as "yes" forming a set Y and submissions classified as "no" forming a set N, and set Y is concatenated before set N to form an initial sorting list L; for the submissions in the initial sorting list L, an insertion sort strategy is used, and pairwise comparisons are performed using the large language model to determine the final position of each submission in the ordered result list R, outputting the final sorting list. The technical solution of this invention filters out code noise, solves the problem of inability to sort multiple candidate submissions internally, and significantly improves the accuracy of vulnerability patch location and the robustness of sorting.

An example method includes obtaining a result of a business application discovery process, where the result lists a plurality of software packages installed on a computing system of an enterprise, identifying a first software package of the plurality of software packages for which an end of service life is scheduled to occur within a defined period of time, identifying a set of business applications of the enterprise that uses the first software package, delivering, for each business application of the set of business applications, a notification to an owner of the each business application alerting the owner to the end of service life for the first software package, wherein the notification includes a hyperlink to a survey about the each business application, collecting responses of the owner to the survey, and generating a dashboard that aggregates the responses with data about other software packages used by the owner.

The application relates to the technical field of data processing, and particularly discloses an online time sequence reserved rain flow counting method, which comprises the following steps: S1, acquiring an original overload sequence; S2, reading four continuous data points in the original overload sequence into a new data set, judging whether a full cycle exists in the new data set, if the full cycle exists, deleting the full cycle from the new data set and recording the full cycle into a cycle result list, and then supplementing two new data points from the original overload sequence into the new data set; if the full cycle does not exist, supplementing one new data point from the original overload sequence into the end of the new data set; S3, taking the last four data points in the new data set as the input of the next round, and repeatedly executing S2 until all data points in the original overload sequence are read and no full cycle exists in the new data set; and S4, arranging all full cycles in the cycle result list of the latest round in time sequence. The application can more efficiently and completely identify and extract the full cycle.

This invention discloses an AI vision-based method for detecting defects in industrial printed circuit boards (PCBs), comprising: acquiring PCB image data and preprocessing it to obtain standardized image data; performing pixel-to-layout topology alignment analysis to generate a priori structural map; constructing an improved EfficientViT network to output multi-layer feature maps; performing spatial and frequency domain feature registration to obtain registered spatial and frequency domain feature maps; constructing an orthogonal anomaly detection module to obtain pixel-level anomaly heatmaps; performing threshold segmentation and connected component extraction to generate a defect result list; writing to traceability records and generating release, re-judgment, or rejection instructions. This invention, by combining the improved EfficientViT network with the orthogonal anomaly detection module, achieves PCB defect detection and traceable closed-loop control.

The application discloses a search optimization method and system based on mixed recall and multi-stage sorting, and a medium, comprising: generating candidate material subsets through multiple recall channels respectively; merging and deduplicating the candidate material subsets output by each recall channel to obtain a full candidate material set; extracting features from the full candidate material set to generate a sorting feature set; using a first sorting model based on the sorting feature set to perform primary sorting on the full candidate material set to generate a primary sorting list; intercepting a first number of materials from the primary sorting list, using a second re-sorting model to perform secondary sorting on the intercepted materials, and outputting a final search result list; the application can use a three-way parallel mixed recall technical solution, combine the recall capabilities of text relevance matching, content quality control, popular behavior adaptation and deep semantic understanding in multiple dimensions, make up for the technical defects of a single recall channel, and greatly improve the coverage and matching accuracy of the recall link.

This invention relates to a software automated testing method, system, and electronic device, belonging to the field of software testing technology. The method includes: obtaining initial test cases by performing correlation analysis with detailed design documents and software architecture design documents, along with the C code and model; obtaining a JSON file by performing structured parsing and semantic compression on the C code and model; using the JSON file and initial test cases as input to a large language model; the large language model outputting a target JSON file; inputting the target JSON file into a credibility assessment module to obtain a test score; if the test score is greater than or equal to a preset score, obtaining a test result list based on the target JSON file and initial test cases. This invention combines a large language model to test various functions of the software during the testing process to obtain a test result list, and uses credibility assessment for filtering, which can effectively improve test coverage and testing efficiency.

This application relates to a hybrid search method, apparatus, electronic device, and storage medium. The method includes: acquiring input data; extracting at least one query term from the input data and searching for target text terms matching the at least one query term in an index; forming a first candidate result list based on candidate images corresponding to the target terms and text relevance; extracting query feature vectors from the input data and searching for target image feature vectors related to the query feature vectors in a vector database; forming a second candidate result list based on candidate images corresponding to the target image feature vectors and cosine similarity; determining a comprehensive score for each candidate image in the first and second candidate result lists based on text relevance and cosine similarity; and generating a search result list for the input data based on the comprehensive score of each candidate image. The solution provided in this application enables the synergy of multimodal retrieval technologies.

The application discloses a re-identification processing method and device for picture search, relates to the technical field of big data analysis and application, and can solve the problem of long time consumption of the pedestrian re-identification processing method in the prior art. The specific technical scheme is as follows: firstly, an initial feature vector of a target re-identification data set is acquired, the initial feature vector comprises an N-dimensional vector, at least one human picture is included in the target re-identification data set, and N is greater than or equal to 1; then, the initial similarity between the initial feature vector and all feature vectors in a preset picture database is calculated, a first similarity result list is obtained, and the current storage capacity of the picture database is N_G; finally, it is judged whether the first similarity result list is all lower than a first preset threshold value; if yes, the initial feature vector is added to the picture database, and N_G is equal to N_G plus 1. The application is used for the re-identification processing of picture search.

This application relates to a product search method, apparatus, device, and medium in the field of e-commerce technology. The method includes: responding to a product search request and obtaining a recall list coarsely recalled based on user-input search keywords; determining the node servers corresponding to each recalled product in the recall list, where each node server caches multiple search-related scores for some recalled products across different dimensions, the search-related scores representing the relevance between the recalled products and the search keywords in a specified dimension; sending a score calculation request to each node server to obtain the search scores calculated by the node servers for the cached recalled products, the search score for each recalled product being calculated based on multiple search-related scores for that product; and constructing a search results list by filtering products from the recall list whose search scores meet preset conditions based on the search scores. This application can quickly and accurately search for products.

An information processing apparatus, an information processing method, and an information processing system. The information processing apparatus is provided with one or more memories that store state information indicating a predetermined state of an object, identification information for an image or video that represents a mode of the predetermined state, and document information including a description describing the mode represented by the image or video, and circuitry that receives from the communication terminal, a search input, transmits to the communication terminal, first screen information of a search result list screen indicating an image or video identified by the identification information of the image or video stored with the state information specified based on the input, receives from the communication terminal, information for specifying an image or video selected by a user, generates description information including a description in the document information stored in association with identification information for the image or video, and transmits the description information to the communication terminal.