Machine learning classifiers to predict the quality of semantic web queries
Gomathi Ramalingam,
Logeswari S,
M. D. Kumar
et al.
Abstract:In this research, a classification framework to automatically identify well and poorly designed SPARQL queries is proposed. Evaluating SPARQL queries becomes a difficult challenging issue because of the query design and the volume of data to be handled. The proposed context applies various machine learning algorithms including decision trees, k nearest neighbours, support vector machine, and naive Bayes. In addition, two different feature extraction techniques called TFIDF measure and count vectorizer are meas… Show more
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