Constructing literature abstracts by computer: techniques and prospects
Information Processing and Management: an International Journal - Special issue on natural language processing and information retrieval
New Methods in Automatic Extracting
Journal of the ACM (JACM)
Introduction to Algorithms
Generating indicative-informative summaries with sumUM
Computational Linguistics - Summarization
Improving Term Extraction by System Combination Using Boosting
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Learn - Filter - Apply - Forget. Mixed Approaches to Named Entity Recognition
NLDB'01 Proceedings of the 6th International Workshop on Applications of Natural Language to Information Systems
Generating natural language summaries from multiple on-line sources: language reuse and regeneration
Generating natural language summaries from multiple on-line sources: language reuse and regeneration
Term extraction + term clustering: an integrated platform for computer-aided terminology
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
Abstract generation based on rhetorical structure extraction
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Producing more readable extracts by revising them
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Intelligent access to text: integrating information extraction technology into text browsers
HLT '01 Proceedings of the first international conference on Human language technology research
Named entity recognition: a maximum entropy approach using global information
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
An Improved Automatic Term Recognition Method for Spanish
CICLing '09 Proceedings of the 10th International Conference on Computational Linguistics and Intelligent Text Processing
Summarization from medical documents: a survey
Artificial Intelligence in Medicine
Multilingual summarization evaluation without human models
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Overview of the INEX 2010 question answering track (QA@INEX)
INEX'10 Proceedings of the 9th international conference on Initiative for the evaluation of XML retrieval: comparative evaluation of focused retrieval
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In this paper we present REG, a graph approach to study a fundamental problem of Natural Language Processing: the automatic summarization of documents. The algorithm models a document as a graph, to obtain weighted sentences. We applied this approach to the INEX@QA 2010 task (question-answering). To do it, we have extracted the terms and name entities from the queries, in order to obtain a list of terms and name entities related with the main topic of the question. Using this strategy, REG obtained good results regarding performance (measured with the automatic evaluation system FRESA) and readability (measured with human evaluation), being one of the seven best systems into the task.