Combination of Features for Vietnamese News Multi-document Summarization
| Autor: | Van-Giau Ung, An-Vinh Luong, Nhi-Thao Tran, Minh-Quoc Nghiem |
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| Rok vydání: | 2015 |
| Předmět: |
Computer science
business.industry Vietnamese Supervised learning computer.software_genre Semantics Automatic summarization language.human_language Set (abstract data type) Multi-document summarization ComputingMethodologies_DOCUMENTANDTEXTPROCESSING language Unsupervised learning Artificial intelligence business computer Sentence Natural language processing |
| Zdroj: | KSE |
| DOI: | 10.1109/kse.2015.71 |
| Popis: | The aim of multi-document summarization is to produce an abridged version which contains important information from a set of documents on the same topic. This paper describes an approach that incorporates a set of features at word and sentence level to extract important sentences from input documents for Vietnamese news multi-document summarization system. Then, the summaries are evaluated automatically by using the ROUGE measure. The obtained result indicates that this approach produces good summaries and is appropriate for Vietnamese as well as languages limited linguistic resources. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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