Research And Implementation Of Learning Resource Retrieval Based On Knowledge-Based Query Expansion And User Feedback

In the face of massive learning resources,traditional keyword-based learning resource retrieval ignores semantic associations,which often leads to inaccurate search results and cannot meet the search needs of learners.Knowledge-based learning resource retrieval can solve this problem.From the depth of retrieval,using knowledge points to describe the semantics of teaching resources facilitates the retrieval of knowledge,which helps the retrieval system to understand the knowledge and semantics of the search content input by learners;In terms of efficiency,the index of learning resources to knowledge points is established offline,and the knowledge point extraction of the retrieved content can respond quickly.Therefore,this paper firstly implements knowledge-based learning resource retrieval,and conducts research on knowledge-based query expansion strategy and knowledge-based feedback strategy in learning resource retrieval.The main contents include:(1)Facing the shortcomings of traditional keyword-based learning resource retrieval,this paper implements knowledge-based learning resource retrieval,constructs a corpus to manage knowledge and learning resources uniformly and effectively,and uses natural language processing technology and latent semantic analysis(LSA)to achieve retrieval content.Mapping of knowledge points and indexing of learning resources to knowledge points,and inverting learning resources to implement knowledge-based learning resource retrieval.(2)Only the knowledge point extraction of the search content may be impossible to map to the knowledge point due to the unknown expression of the learner,resulting in too little or no search resource.This paper proposes a knowledge-based query expansion strategy,which uses the synonym expansion to explain and supplement the semantic content of the search content,and uses the knowledge base to expand and filter the synonym and further expand the query based on the knowledge structure to mine the query-related,combines the two parts to achieve knowledge-based query expansion.(3)When the learner conducts the learning resource search,there may be insufficient satisfaction with the search results,but the search results cannot be corrected,and the learner abandons the use of the learning resource retrieval.This paper proposes a retrieval mechanism for relevant feedback of search results.The relevant feedback makes the search results closer to the query requirements.On the one hand,the relevant knowledge points are adjusted by multiple rounds of related feedback,so that the presented learning resources are more in line with the learners.On the other hand,the multi-person related feedback is used to correct the index of learning resources to knowledge points,so that the knowledge-based learning resource retrieval results are more credible.In addition to the above research,this paper also builds a knowledge extension feedback retrieval system.On the basis of implementing knowledge-based learning resource retrieval,the knowledge query extension and the learner's related feedback function are added to it,and the system collects relevant data and utilizes it.The data validates the relevant research methods.