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dc.contributor.authorAbghari, Arash 13:35:46 (GMT) 13:35:46 (GMT)
dc.description.abstractThis work is an attempt to enhance query classification in call routing applications. A new method has been introduced to learn weights from training data by means of a regression model. This work has investigated applying the tf-idf weighting method, but the approach is not limited to a specific method and can be used for any weighting scheme. Empirical evaluations with several classifiers including Support Vector Machines (SVM), Maximum Entropy, Naive Bayes, and k-Nearest Neighbor (k-NN) show substantial improvement in both macro and micro F1 measures.en
dc.publisherUniversity of Waterlooen
dc.subjectQuery Classificationen
dc.subjectWeight learningen
dc.titleImproving Query Classification by Features’ Weight Learningen
dc.typeMaster Thesisen
dc.subject.programElectrical and Computer Engineeringen and Computer Engineeringen
uws-etd.degreeMaster of Applied Scienceen

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