Free Model of Sentence Classifier for Automatic Extraction of Topic Sentences  

Oleh:

Khodra, M.L. ; Widyantoro, D.H. ; Aziz, E.A. ; Trilaksono, B.R.

Jenis: Article from Journal - ilmiah nasional - terakreditasi DIKTI
Dalam koleksi: Journal of ICT Research and Applications vol. 5C no. 1 (2011), page 17-34.
Topik: Automatic Extraction; Sentence Classifier; SVM; Topic Sentence
Fulltext: 1_Thom.pdf (561.58KB)

Isi artikel

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.

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