Automatic Text Summarization for Indonesian Language Using TextTeaser

D Gunawan, A Pasaribu, R F Rahmat, R Budiarto


Text summarization is one of the solution for information overload. Reducing text without losing the meaning not only can save time to read, but also maintain the reader’s understanding. One of many algorithms to summarize text is TextTeaser. Originally, this algorithm is intended to be used for text in English. However, due to TextTeaser algorithm does not consider the meaning of the text, we implement this algorithm for text in Indonesian language. This algorithm calculates four elements, such as title feature, sentence length, sentence position and keyword frequency. We utilize TextRank, an unsupervised and language independent text summarization algorithm, to evaluate the summarized text yielded by TextTeaser. The result shows that the TextTeaser algorithm needs more improvement to obtain better accuracy.

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