Xiaohui Zou
Shunpeng Zou
ABSTRACT
The purpose of this paper is to introduce a new approach that must cover all the terms. Therefore, people's educational process is like making a variety of choices in a super-chessboard of language or a matrix composed of words formally. The method of redemption is: First, construct the chessboard, and then, through human-computer interaction and collaboration, generate massive amounts of big data, including various terms representing knowledge, and finally, through machine learning and man-machine interactive to analyze, compare, and query or reuse any of these terms. The result: an accurate query of terms, which can be automatically queried in multiple ways through bilingual or multi-lingual converters. The significance is that the method and its results can be used not only for machine-assisted instruction in the network environment, but also for machine-assisted intelligent text analysis and knowledge module finishing in the network environment, thus opening up view of big data and education. The new approach, because any term must be in the word matrix, each user and its agents query them very accurately and efficiently.
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