Advances in Automatic Text Summarization
Advances in Automatic Text Summarization
NEO-CORTEX: A Performant User-Oriented Multi-Document Summarization System
CICLing '07 Proceedings of the 8th International Conference on Computational Linguistics and Intelligent Text Processing
Multilingual summarization evaluation without human models
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Text Mining: Predictive Methods for Analyzing Unstructured Information
Text Mining: Predictive Methods for Analyzing Unstructured Information
Extractive summarization based on word information and sentence position
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
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In this paper we briefly describe two summarizers: ResúmeME and GIL-UNAM-3. Both are used to extract utterances from a set of documents retrieved by means of synonym modified queries. That is, we modify each query by obtaining from the WordNet database word synonyms for each of its words. The queries are provided by the QA@INEX 2010 task. The results of the experiments are evaluated automatically by means of the FRESA system.