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REDES: Reconocimiento de Entidades Digitales: Enriquecimiento y Seguimiento mediante Tecnologías del Lenguaje ; REDES: Digital Entities Recognition: Enrichment and Tracking by Language Technologies
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A novel concept-level approach for ultra-concise opinion summarization
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Sentiment classification for early detection of health alerts in the chemical textile domain
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LEGOLANG: técnicas de deconstrucción aplicadas a las tecnologías del lenguaje humano ; LEGOLANG: deconstruction techniques applied to human language technologies
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EMOTIBLOG: a model to learn subjetive information detection in the new textual genres of the web 2.0 -a multilingual and multi-genre approach
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TextMess 2.0: las tecnologías del lenguaje humano ante los nuevos retos de la comunicación digital ; TextMess 2.0: the new digital media challenges facing human language technologies
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EMOCause: an easy-adaptable approach to emotion cause contexts
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Araknion: inducción de modelos lingüísticos a partir de corpora ; Araknion: inducing linguistics models from corpora
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Evaluating the robustness of EmotiBlog for sentiment analysis and opinion mining
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TextMess 2.0: Las Tecnologías del Lenguaje Humano ante los nuevos retos de la comunicación digital
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TextMess 2.0: Las Tecnologías del Lenguaje Humano ante los nuevos retos de la comunicación digital
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EmotiBlog: a finer-grained and more precise learning of subjectivity expression models
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Going beyond traditional QA systems: challenges and keys in opinion question answering
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AQA: a multilingual anaphora annotation scheme for question answering ; AQA: un modelo de anotación anafórico multilingüe para búsqueda de respuestas
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TEXT-MESS: Intelligent, Interactive and Multilingual Text Mining based on Human Language Technologies, TIN2006-15265-C06
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Enhancing QA systems with complex temporal question processing capabilities
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Abstract:
This paper presents a multilayered architecture that enhances the capabilities of current QA systems and allows different types of complex questions or queries to be processed. The answers to these questions need to be gathered from factual information scattered throughout different documents. Specifically, we designed a specialized layer to process the different types of temporal questions. Complex temporal questions are first decomposed into simple questions, according to the temporal relations expressed in the original question. In the same way, the answers to the resulting simple questions are recomposed, fulfilling the temporal restrictions of the original complex question. A novel aspect of this approach resides in the decomposition which uses a minimal quantity of resources, with the final aim of obtaining a portable platform that is easily extensible to other languages. In this paper we also present a methodology for evaluation of the decomposition of the questions as well as the ability of the implemented temporal layer to perform at a multilingual level. The temporal layer was first performed for English, then evaluated and compared with: a) a general purpose QA system (F-measure 65.47% for QA plus English temporal layer vs. 38.01% for the general QA system), and b) a well-known QA system. Much better results were obtained for temporal questions with the multilayered system. This system was therefore extended to Spanish and very good results were again obtained in the evaluation (F-measure 40.36% for QA plus Spanish temporal layer vs. 22.94% for the general QA system). ; This paper has been partially supported by the Spanish government, project TIN-2006-15265-C06-01, and by the framework of the project QALL-ME, which is a 6th Framework Research Programme of the European Union (EU), contract number: FP6-IST-033860.
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Keyword:
Complex temporal questions; Lenguajes y Sistemas Informáticos; Processing; QA systems
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URL: http://hdl.handle.net/10045/22488 https://doi.org/10.1613/jair.2805
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Machine learning techniques for automatic opinion detection in non-traditional textual genres
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Opinion and generic question answering systems: a performance analysis
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