Supervised Opinion Frames Detection with RAID
作者： Alessio Palmero Aprosio , Francesco Corcoglioniti , Mauro Dragoni , Marco Rospocher
DOI: 10.1007/978-3-319-25518-7_22
关键词: Lexicon 、 Dependency grammar 、 Natural language processing 、 Data mining 、 Frame (artificial intelligence) 、 Semantic analysis (machine learning) 、 Artificial intelligence 、 Pipeline (software) 、 RAID 、 Named-entity recognition 、 Conditional random field 、 Computer science
摘要: Most systems for opinion analysis focus on the classification of polarities and rarely consider task identifying different elements relations forming an frame. In this paper, we present RAID, a tool featuring processing pipeline extraction frames from text with their expressions, holders, targets polarities. RAID leverages lexical, syntactic semantic text, using several NLP tools such as dependency parsing, role labelling, named entity recognition word sense disambiguation. addition, linguistic resources SenticNet MPQA Subjectivity Lexicon are used both to locate opinions in classify according fuzzy model that combines sentiment values words. was evaluated three datasets is released open source software under GPLv3 license.
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