In everyday life, multi-document summarization (MDS) methods are becoming tremendous
attention in different fields, especially for online documents, because this online document …

Automatic multi-document summarization needs to find representative sentences not only by
sentence distribution to select the most important sentence but also by how informative a …

In this paper, we proposed a work onrhetorical corpus construction andsentence
classification model experiment that specifically could be incorporated in automatic paper …

Document clustering based on topic similarities helps users in searching from a collection of
scientific articles. Topic labels are necessesary for describing subjects of the document …

Sentence extraction in news document summarization determines representative sentences
primarily by employing the news feature known as news feature score (NeFS). NeFS can …

With the increasing number of online comments, it was hard for buyers to find useful
information in a short time so it made sense to do research on automatic summarization …

Abstract News Feature Scoring (NeFS) merupakan metode pembobotan kalimat yang sering
digunakan untuk melakukan pembobotan kalimat pada peringkasan dokumen berdasarkan …

Banking operational services are supported by a banking information system called Core
Banking System (CBS). Due to frequent request from branches without accompanied by …

Sebagian besar hasil ringkasan multi dokumen yang menggunakan metode extractive
summary, yaitu dengan mengambil kalimat-kalimat penting dari dokumen, sering kali tidak …

Sentence distribution method performs weighting based on the sentence distribution without
taking the semantic meaning of the sentence spread into account. In fact, the semantic …