2006 · 11 citations · 8 references
EngineeringTerm Co-occurrenceEntity SummarizationNarrative SummarizationCorpus LinguisticsText MiningAutomatic SummarizationNatural Language ProcessingLanguage DocumentationInformation RetrievalBetter SummarizationText SummarizationComputational LinguisticsLanguage StudiesLinkage InformationContent AnalysisTerminology ExtractionMulti-modal SummarizationSubject InformationKeyword ExtractionLinguistics
As the amount of textual information available grows rapidly, automatic text summarization methods are becoming increasingly important. Based on the subject information from term co-occurrence graph and linkage information of different subjects, a novel automatic summarization algorithm is proposed in this paper. This algorithm can get better summarization and can be adaptable to different document style. And it also can pick up subject information, whose significance was evaluated in accordance to the rules presented in this paper. Besides, it can dynamically decide the summary size. The validity of the algorithm has been tested, showing that the novel automatic text summarization algorithm tallies with author's intentional subjects and is information-redundancy-free
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The Automatic Creation of Literature Abstracts
H. P. Luhn · IBM Journal of Research and Development · 1958 · 3.2K citations
New Methods in Automatic Extracting
H. P. Edmundson · Journal of the ACM · 1969 · 1.5K citations
Automatic text structuring and summarization
Gerard Salton, Amit Singhal, Mandar Mitra et al. · Information Processing & Management · 1997 · 496 citations · Full text