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Free Model of Sentence Classifier for Automatic Extraction of Topic Sentences
M.L. Khodra1, D.H. Widyantoro1, E.A. Aziz2 & B.R. Trilaksono1
1School of Electrical Engineering and Informatics,
Bandung Institute of Technology, Indonesia
2Faculty of Language and Arts Education,
Indonesia University of Education, Indonesia
Email: masayu@informatika.org
Abstract. This research employs free model that uses only sentential features without paragraph context to extract topic sentences of a paragraph. For finding optimal combination of features, corpus-based classification is used for constructing a sentence classifier as the model. The sentence classifier is trained by using Support Vector Machine (SVM). The experiment shows that position and meta-discourse features are more important than syntactic features to extract topic sentence, and the best performer (80.68%) is SVM classifier with all features.
Keywords: automatic extraction; sentence classifier; SVM; topic sentence.
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