We study correlation of rankings of text summarization systems using evaluation methods with and without human models. We apply our comparison framework to various well-establishe...
Horacio Saggion, Juan Manuel Torres Moreno, Iria d...
Abstract. Evaluation is one of the hardest tasks in automatic text summarization. It is perhaps even harder to determine how much a particular component of a summarization system c...
Extracting sentences that contain important information from a document is a form of text summarization. The technique is the key to the automatic generation of summaries similar ...
Text Summarization and categorization have always been two of the most demanding information retrieval tasks. Deploying a generalized, multifunctional mechanism that produces good ...
A key problem in text summarization is finding a salience function which determines what information in the source should be included in the summary. This paper describes the use ...
Abstract. This paper presents how text summarization can be influenced by textual entailment. We show that if we use textual entailment recognition together with text summarization...
Terms, term relevances, and sentence relevances are concepts that figure in many NLP applications, such as Text Summarization. These concepts are implemented in various ways, thou...
Abstract. We describe a text summarization system that moves beyond standard approaches by using a hybrid approach of linguistic and statistical analysis and by employing text-sort...
Text summarization is a data reduction process. The use of text summarization enables users to reduce the amount of text that must be read while still assimilating the core inform...
Lawrence H. Reeve, Hyoil Han, Saya V. Nagori, Jona...