Free Model of Sentence Classifier for Automatic Extraction of Topic Sentences | Zendy

Masayu Leylia Khodra | Zendy; Dwi H. Widyantoro | Zendy; E. Aminudin Aziz | Zendy; Bambang Riyanto Trilaksono | Zendy

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Free Model of Sentence Classifier for Automatic Extraction of Topic Sentences

Author(s) -

Masayu Leylia Khodra,

Dwi H. Widyantoro,

E. Aminudin Aziz,

Bambang Riyanto Trilaksono

Publication year - 2011

Publication title -

itb journal of information and communication technology

Language(s) - English

Resource type - Journals

ISSN - 1978-3086

DOI - 10.5614/itbj.ict.2011.5.1.2

Subject(s) - paragraph , sentence , computer science , classifier (uml) , artificial intelligence , support vector machine , natural language processing , quadratic classifier , speech recognition , world wide web

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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