A system and method for semantic prefetch of resource cloud storage for educational domain

Abstract

The invention provides a semantic prefetching system and a semantic prefetching method for resource cloud storage in the educational field. The system comprises a user interface module, a request control module, a cloud storage module, a buffer management module, a replica management module and a prefetching module. The method comprises the following steps: user requests concept acquisition, concept set topic relevance judgment, candidate center concept selection, center concept determination, prefetch object determination, prefetch storage target node determination, prefetch window size and topic relevance maintenance, conversion, disappearance and stopping prefetching. Aiming at the shortcomings of the cloud storage method in the education field, the invention combines the characteristics of the education resources to form a specific education cloud storage system.

Description

technical field [0001] The invention belongs to the semantic prefetching technology of resource cloud storage in the educational field, and in particular relates to a semantic prefetching system and method for resource cloud storage in the educational field. Background technique [0002] In recent years, cloud computing has developed rapidly, and as an important part of cloud computing, cloud storage has become one of the current hot research topics. At present, the research on cloud storage mainly focuses on data storage and improving storage performance, but less attention is paid to storage efficiency research in the case of storage objects limited to domains. According to the general rules, storage efficiency research mainly needs to solve the network delay and network service quality problems of resource requests. The current solutions include caching and prefetching. For resources in the education field, we found that there are characteristics such as access object th...

AI Technical Summary

Problems solved by technology

[0025] 1. Existing data prefetching technologies are mainly oriented to the general field, relying on user behavior data and simple resource categories to prefetch resources, and the amount of information that these data can explain is very limited. When the system predicts the central concept of resources Deviations are prone to occur, affecting the prefetching of educational resources required by users, making users unable to find or obtain irrelevant resources when they have learning needs, which is not conducive to the development of learning behaviors

[0026] 2. In addition to the accuracy of resources, the determination of nodes for general cloud storage system solutions is not clear enough, especially educational resources have the characteristics of access object theme and behavior aggregation, and simply determining the scheduling nodes of resources is far from enough , it is necessary to further determine the target node to meet the user's learning needs

[0027] 3. For educational resources, after using the technology of semantic tag retrieval, the amount of information to be retrieved will increase. If certain measures are not taken, the time used will be much longer than that of traditional retrieval methods. When encountering some time-sensitive When selecting a strong resource, it will spend a lot of time on the retrieval and delivery of the resource and miss the opportunity; in addition, when selecting the central concept, only through the associated value without considering the specific scope and timeliness of the resource will also affect the effectiveness of the resource

Images