Big data acquisition multi-core parameter adaptive time-sharing memory driving method and system

Abstract

The invention provides a big data acquisition multi-core parameter self-adaptive time-sharing memory driving method and a big data acquisition multi-core parameter self-adaptive time-sharing memory driving system. The scheme comprises the steps of logging in through an account password, obtaining current learning times, carrying out word learning, generating review prompt time of words, testing questions, testing correct answers and testing answer time limitation; after the user finishes the review task, generating a memory index of each word and the current memory intensity of each word; according to the memory index, the memory intensity and the current memory stock, generating a memory stock extraction function, and calculating time points of golden memory in each memory period; extracting historical test data, obtaining a target training function through historical data training, and determining golden memory time of all users; and comprehensively generating a comprehensive memory intensity score of each word. According to the scheme, word memory is performed in a targeted manner through a plurality of core parameters such as learning times, error times and memory intensity, and reasonable review time of each student is given, so that the memory efficiency of the students is improved.

Description

technical field [0001] The present invention relates to the technical field of foreign language memory, and more specifically, to a large data collection multi-core parameter self-adaptive time-sharing memory driving method and system. Background technique [0002] Memory is the foundation of learning and plays an important role for everyone. In particular, in the current youth education process, how to effectively use and improve one's own memory ability plays an important role in improving the academic performance of young people. Foreign language learning is an important part of education, and its requirements for memory are higher than those of other subjects in the learning process. Therefore, a large number of words and vocabulary, and even sentences need to be memorized by force. Word memorization has become an important hurdle in foreign language learning. [0003] Most of the existing memory methods rely on the existing theoretical knowledge and judge the student...

AI Technical Summary

Problems solved by technology

[0003] Most of the existing memory methods rely on the existing theoretical knowledge and judge the students' learning status according to the preset experience, but cannot know the actual learning status of each student, and then give targeted suggestions for learning and review Time, and targeted test questions, resulting in the learning process can only guess the learning level of each word based on experience, and subjectively judge whether each word has been learned, or whether it has been learned

It leads to repeated learning of words that are known, and repeated forgetting of words that are not

On the one hand, it reduces the learning efficiency, on the other hand, it also reduces the number of reviews and increases the possibility of forgetting

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