5 results about "Attribute weight" patented technology

The application provides a material similarity analysis method based on a semantic library and a knowledge graph, comprising the following steps: S1: judging whether the decisive attributes of two materials are similar, if any of the decisive attributes is not similar, then the two materials are non-redundant materials, otherwise, entering S2; S2: calculating the similarity of the field part according to the non-decisive attribute weight and the distance of each field; S3: combining all the knowledge graph paths and weight values to calculate the similarity of the graph part; S4: adding the similarity of the field part and the similarity of the graph part to obtain the final material similarity, and judging whether the two materials are high similarity through the final material similarity. The material similarity analysis method provided by the application optimizes the accuracy of the similarity algorithm.

A price analysis method and system based on a multi-attribute template, comprising: constructing a multi-attribute template, generating attribute weights and coding rules through association rule mining, and fusing commodity descriptions and business fields into attribute vectors; calculating similarity based on weighted Euclidean distance, normalizing attention weight through Softmax, and weighting and summing historical prices to obtain reference price; calculating deviation rate and comparing with threshold value to perform hierarchical disposal; constructing a knowledge graph to detect associated abnormalities and price avoidance paths; and implementing batch backtracking based on a version-identified feature cache table. The present application realizes fine-grained price analysis and hidden abnormality mining, and supports dynamic template updating, coding rule adaptive calibration and multi-level rollback mechanisms, significantly improving system robustness and cold start capability.

Embodiments of the present application provide a list data filtering method and device, electronic equipment and readable storage medium, and relate to the technical field of computer. The method comprises: determining at least one candidate list data from the to-be-filtered list according to a target screening condition, and then determining invalid attributes that do not match at least one target attribute from a plurality of preset attributes based on the at least one target attribute corresponding to the target screening condition. The attribute weight of each target attribute can be improved according to the initial weight of the invalid attribute to obtain the first attribute weight corresponding to each target attribute, and then the list data weight of each candidate list data is obtained according to the first attribute weight corresponding to each target attribute. The final valid list data is determined by judging whether the list data weight is greater than a preset list data weight threshold, thereby improving the accuracy of list data screening and making the screened list data more application valuable.

This invention provides a method, apparatus, device, and medium for personalized configuration of delivery confirmation methods, including: constructing a multi-dimensional attribute library for packages; extracting package attributes corresponding to a target package based on the constructed multi-dimensional attribute library; constructing a feature vector for the target package based on the package attributes of the target package and the logical relationships between the attributes; and completing intelligent matching and decision-making of delivery confirmation rules based on the feature vector of the target package, combined with the global attribute weights corresponding to each package attribute of the target package and a digital delivery confirmation rule library. This invention addresses industry pain points such as rigid processes, insufficient intelligence, significant system performance shortcomings, and poor adaptability to complex scenarios in traditional logistics delivery confirmation models. Through a complete technical system encompassing multi-dimensional attribute modeling, weighted intelligent matching, LLM for complex scenarios, high-frequency rule caching, and high-concurrency traffic control, it achieves precise personalized configuration of delivery confirmation methods and efficient and stable system operation.

This invention discloses a comprehensive log collection and maintenance method and system, relating to the field of intelligent operation and maintenance technology. The method includes: collecting multi-source log data and performing standardization processing to generate standardized log data; calculating information gain to generate attribute weights based on the standardized log data; calculating multi-class attribute distances using K-Prototype clustering to generate a final weighted distance to obtain a clustering dataset; optimizing the GNN model using the PGNN framework combined with a graph attention mechanism to output an optimized clustering dataset; generating anomaly candidate clusters based on the optimized clustering dataset; extracting anomaly characteristics of the anomaly candidate clusters; and classifying the anomaly characteristics of the anomaly candidate clusters using a K-NN classifier to obtain the data point classification results. This invention improves the accuracy and response speed of anomaly log identification, achieving more efficient log management.