Linguistic Knowledge Based Supervised Key - phrase Extraction
نویسندگان
چکیده
The most important information about the content of a document is represented by the key phrases of that document. In this study an automatic key phrase extraction algorithm is devised using machine learning technique. The proposed method not only considers the document level statistics like TFxIDF, the linguistic features of the phrases are also incorporated. Experiment has been performed on Naïve Bayes’ classifier, J48 Decision Tree, and IBk lazy learner to choose the most suitable learning model. The imbalanced class distribution problem is resolved by over sampling on the minority class samples synthetically. The experimental result reveals the accuracy and efficiency of the proposed technique.
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