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main issue is related to the management and classification of information provided by users. This paper introduces a folksonomy approach, the architecture of the system, and the results of an experiment about keyword recommendations.
How to find the teaching resources according to users' demand quickly and accurately on the Internet is urgent to be solved. This paper proposes a design of pretreatment for keyword-based search over network teaching resource database based on ontology. Firstly, the teaching ontology is created according to the
detail. The paper presents the similarity algorithm of domain keywords and common words respectively and integrates them into the question similarity. Experimental results show that the proposed method can achieve good performance and the system is applied.
result based on string matching keyword based. Precision and recall of this method is low. This research proposes subject name search based on document content using weighted ontology. Ontology is built from extracted term. Each term is given a weight based on the number of its relation. User query is expanded based on its
search efficiency. A prototype system has been implemented in light of this approach. Given a keyword combined query, the system outputs a ranked list of relative results according to the semantic similarity. In the experiment, the system achieved the better result than traditional keyword based search.
Using automatic extraction of keywords and semi-automatic creation of domain ontologies it is possible to achieve a richer description of learning resources, with positive effects on subsequent searches. Based on this concept, we developed a repository named TREE - Teaching Resources for Engineering Education, to
take advantage of the accurate description of concept as well as the definition of the relationship of the concepts, to expand keywords and improve the accuracy and recall rates.
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