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What Motivates You? Benchmarking Automatic Detection of Basic Needs from Short Posts ...
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Five Psycholinguistic Characteristics for Better Interaction with Users ...
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UH-PRHLT at SemEval-2016 Task 3: Combining Lexical and Semantic-based Features for Community Question Answering ...
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A Resource-Light Method for Cross-Lingual Semantic Textual Similarity ...
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A Low Dimensionality Representation for Language Variety Identification
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A resource-light method for cross-lingual semantic textual similarity
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Semantically-informed distance and similarity measures for paraphrase plagiarism identification
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A Cross-domain and Cross-language Knowledge-based Representation of Text and its Meaning
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A Systematic Study of Knowledge Graph Analysis for Cross-language Plagiarism Detection
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Cross-language Plagiarism Detection over Continuous-space- and Knowledge Graph-based Representations of Language
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Language variety identification using distributed representations of words and documents
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Cross-domain polarity classification using a knowledge-enhanced meta-classifier
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Abstract:
"NOTICE: this is the author’s version of a work that was accepted for publication in Knowledge-Based Systems. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in KNOWLEDGE-BASED SYSTEMS [Volume 86, September 2015, Pages 46–56] DOI http://dx.doi.org/10.1016/j.knosys.2015.05.020 ; In this paper, we propose the use of meta-learning to combine and enrich those approaches by adding also other knowledge-based features. In addition to the aforementioned classical approaches, our system uses the BabelNet multilingual semantic network to generate features derived from word sense disambiguation and vocabulary expansion. Experimental results show state-of-theart performance on single and cross-domain polarity classification. ; This research has been carried out in the framework of the European Commission WIQ-EI IRSES (No. 269180) and DIANA-APPLICATIONS - Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01) projects. This research is partially funded by the national project ACOGEUS (TIN2012-38536-C03-02) and the regional project AORESCU (P11-TIC-7684 MO). We thank Juan M. Cotelo and Luis A. Leiva for their support and comments. ; Franco-Salvador, M.; Cruz, FL.; Troyano Jiménez, JA.; Rosso, P. (2015). Cross-domain polarity classification using a knowledge-enhanced meta-classifier. Knowledge-Based Systems. 86:46-56. https://doi.org/10.1016/j.knosys.2015.05.020 ; S ; 46 ; 56 ; 86
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Keyword:
Cross-domain polarity classification; LENGUAJES Y SISTEMAS INFORMATICOS; Meta-learning; Semantic network; Sentiment analysis; Word sense disambiguation
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URL: https://doi.org/10.1016/j.knosys.2015.05.020 http://hdl.handle.net/10251/63907
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Detección de plagio translingüe utilizando una red semántica multilingüe
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Análisis de similitud basado en grafos: una nueva aproximación a la detección de plagio translingüe ; Graph-based similarity analysis: a new approach to cross-language plagiarism detection
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Knowledge Graphs as Context Models: Improving the Detection of Cross-Language Plagiarism with Paraphrasing
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Cross-language plagiarism detection using multilingual semantic network
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Análisis de similitud basado en grafos: Una nueva aproximación a la detección de plagio translingüe ; Graph-Based Similarity Analysis: A New Approach to Cross-Language Plagiarism Detection
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Detección de plagio translingüe utilizando el diccionario estadístico de BabelNet ; Cross-language Plagiarism Detection Using BabelNet’s Statistical Dictionary
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