6results about How to "Improve resource usage efficiency" patented technology

The invention discloses a big data management method and system based on semantic analysis, and relates to the technical field of big data management. A multilayer semantic abstract data organization structure comprising a base layer, a mode layer and a statistical layer is constructed, real-time semantic analysis is performed on input data, and semantic descriptors are generated; the high-frequency data instance in the base layer is stored to a corresponding level according to a central semantic index, a semantic folding operation is triggered based on a preset rule, the high-frequency data instance in the base layer is automatically abstracted into a modeled representation of a mode layer, and similar representations in the mode layer are further aggregated into an aggregated representation of a statistical layer; when the query is responded, the system analyzes a query intention and determines a target data abstraction level, high-level aggregation or modeling representation is restored into bottom-layer detailed data as required through reverse expansion operation, and a query result is generated; through the multi-layer semantic abstract data organization structure and the data folding operation, the storage efficiency of mass complex data and the performance of multi-granularity intelligent query are effectively improved.

The application relates to the technical field of data processing, can be applied to business scenes such as financial technology and medical health, and discloses a data hierarchical storage method and device based on access representation, equipment and a medium, which comprises the following steps: collecting access behavior features of original data, identifying the heat state, writing data into a matched first target storage equipment according to a preset equipment performance corresponding relationship; after data storage, continuously monitoring subsequent access features, dynamically judging whether the heat state changes; if the heat state changes and meets specific migration conditions, a second target storage equipment is re-allocated and a data migration operation is completed, so that automatic hierarchical storage management of cold and hot data is realized. Through the acquisition of data access representation and the dynamic identification of the heat state, hierarchical migration of different heat data between different performance storage equipment is realized, the resource use efficiency and the access performance of the storage system are improved, and the storage cost is reduced.

A source base station and a transmission method. A source base station transmits a radio resource control reconfiguration message to a user equipment. The radio resource control reconfiguration message includes an indication message and a candidate base station list, and the candidate base station list is used for indicating a plurality of candidate base stations. The source base station determines a non-target base station among the plurality of candidate base stations based on a prediction report received from the user equipment. And the source base station transmits a handover cancellation request to the non-target base station in the plurality of candidate base stations, so that the non-target base station releases a reserved resource corresponding to the user equipment. The transmission technology provided by the invention can improve the resource use efficiency of the mobile communication system.

The embodiment of the invention provides a data scheduling method, a data access method, a cloud storage platform and computing device.The data scheduling method is applied to a data scheduling end of the cloud storage platform and comprises the steps of obtaining historical use data of resources on at least one cloud storage service cluster, acquiring historical access data of a plurality of storage containers on at least one cloud storage service cluster; performing data analysis based on the historical use data and the historical access data, and predicting a matching relationship between the at least one cloud storage service cluster and the plurality of storage containers in a target time period; based on the matching relationship, the plurality of storage containers are deployed on the corresponding target cloud storage service clusters, and the resource use condition of each cloud storage service cluster and the access demand of the storage container are predicted in advance through data analysis of the historical use data and the historical access data, so that reasonable container deployment is completed in advance, and the user experience is improved. The problem of service response delay is solved, and the resource use efficiency and the overall performance of the cloud storage platform are improved.

The application relates to a database backup machine incremental reconstruction idempotent retry method and device. The method comprises the following steps: dividing a reconstruction process into three stages of pre-preparation, intermediate transmission and post-closing, and allowing retry only in the first two stages; first calculating and persisting a master-standby common WAL consistency site common-checkpoint and a difference structure filemap, then sequentially copying a WAL, a serialized change-block mirror and a filemaptarget to a disk; after fault recovery, reverse serializing and continuing transmission, realizing incremental level idempotent retry; if the error context is the same for two times in succession, immediately converging. Through accurate retry control and state persistence, the application significantly reduces the full amount construction triggering probability, improves the data consistency guarantee capability, simultaneously has the non-invasive integration advantage, and can effectively improve the availability and operation and maintenance efficiency of a database system.

This invention relates to the field of financial marketing technology, specifically to an integrated financial marketing management method and system based on marketing data domains. The method includes the following steps: collecting customer transaction and preference data, calculating the magnitude of change and normalizing it into feature vectors; analyzing group differences, calculating the rate of change, and generating a judgment result; combining lifecycle data clustering stage numbers and conversion progress matching rhythm parameters to generate personalized marketing plans; calculating ad placement frequency and consultant service ratio according to multi-group needs for optimized resource allocation; collecting interaction and transaction data after resource allocation, inputting it into a regression model for analysis, and generating marketing effectiveness evaluation results. In this invention, by collecting customer transaction and preference data, quantifying changes, and normalizing them into feature vectors, analyzing group differences to dynamically identify states, combining lifecycle clustering matching rhythm parameters to generate strategies, optimizing ad placement frequency and consultant service ratio according to group needs, and using regression analysis to form a closed-loop optimization management system.