Ontology-based dual-context matching method and system

Abstract

The invention discloses an ontology-based dual-context matching method and system. The method specifically includes: merging the resource context ontology framework and the learning context ontology framework to form a unified context ontology tree; using the context ontology tree to establish a resource context tree and learning Node mapping of the context tree; perceiving the learning context, extracting resource contexts for matching; using context reasoning rules and combining the similarity of the top-level subtrees, sorting the resource contexts; determining the resource context that best matches the current learning context according to the sorting results. The present invention also provides a system for realizing the above method. The present invention uses ontology language to describe the resource situation and the learning situation, and mainly adopts a combination method of logic reasoning, ontology-based reasoning and ontology matching to realize the two-way matching of the resource situation and the learning situation. The dual-situation matching of the present invention not only reduces the matching steps and improves the efficiency, but also reduces the risk of errors in the matching and improves the matching degree of resources and situations.

Description

technical field [0001] The invention relates to the technical field of educational informationization, in particular to an ontology-based dual-scenario matching method. Background technique [0002] Situational cognition theory holds that the situation is the basis of all cognitive activities, and effective learning cannot be separated from the specific situation. Knowledge is contextualized and is continuously developed in activities and applications. Knowledge out of context makes it difficult for learners to apply this knowledge in specific situations and achieve meaningful learning. Conversely, when the learners are provided with situation-related knowledge information, the tacit knowledge within the learners will promote the learners to establish associations with similar situations in the past, so as to adopt similar behaviors when solving problems, and then promote the application of knowledge in specific scenarios. the application of learning, the development of lea...

AI Technical Summary

Problems solved by technology

The process of transforming the learning situation into the characteristics of the target resource depends on human experience and set rules. Not only is it difficult to take into account all situations, but also it is easy to lose some information during the transformation process, and it is difficult to avoid errors.

Moreover, the feature matching between resources often has errors due to the limitations of the algorithm.

In addition, due to the existence of the conversion link, as the number of resources continues to increase, the effectiveness of resource acquisition will be affected

It can be seen that the accuracy and efficiency of the single-context matching method are all limited.

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