There are few research on Vietnamese text summarization. Most of them used the extraction approach, which selects a subset of existing words, phrases, or sentences in the original text to form the summary. The goal of the CLC summarization team is to create a summary that is closer to what a human might generate, a summary that might contain words not explicitly present in the original.
We are focusing on three sub-problems of automatic text summarization: multi-document summarization, sentence fusion, and sentence compression.
- Multi-document summarization system generates a summary from many documents on the same topic or the same event [2, 4].
- Sentence fusion is a method that generate a short single sentence summary from a group of similar sentences .
- Sentence compression aims to remove unnecessary words/phrases from a sentence while keeping the sentence grammatically correct .
 An-Vinh Luong, Nhi-Thao Tran, Van-Giau Ung and Minh-Quoc Nghiem (2015). Word Graph-Based Multi-Sentence Compression: Re-ranking Candidates Using Frequent Words. In: Ho Chi Minh city, Vietnam: The Seventh International Conference On Knowledge And Systems Engineering – KSE2015, in press
 Van-Giau Ung, An-Vinh Luong, Nhi-Thao Tran and Minh-Quoc Nghiem (2015). Combination of Features for Vietnamese News Multi-Document Summarization. In: Ho Chi Minh city, Vietnam: The Seventh International Conference On Knowledge And Systems Engineering – KSE2015, in press
 Nhi-Thao Tran, Van-Giau Ung, An-Vinh Luong, Minh-Quoc Nghiem and Ngan Nguyen. Improving Vietnamese Sentence Compression by Segmenting Meaning Chunks. In: Ho Chi Minh city, Vietnam: The Seventh International Conference On Knowledge And Systems Engineering – KSE2015, in press.
 Hy Nguyen, Tung Le, Viet-Thang Luong, Minh-Quoc Nghiem, and Dien Dinh. The Combination of Similarity Measures for Extractive Summarization. The Seventh International Symposium on Information and Communication Technology (SoICT ’16), December 08-09, 2016, Hochiminh City, Vietnam, © 2016 ACM. ISBN 978-1-4503-4815-7/16/12.