Identifying Collocations for Recognizing Opinions
作者： J. Wiebe
DOI:
关键词: Subjectivity 、 Computer science 、 Linguistics 、 Language identification 、 Natural language processing 、 Information extraction 、 Universal Networking Language 、 Question answering 、 Artificial intelligence 、 Natural language
摘要: Subjectivity in natural language refers to aspects of used express opinions and evaluations (Banfield, 1982; Wiebe, 1994). There are numerous applications for which knowledge subjectivity is relevant, including genre detection, information extraction, retrieval. This paper shows promising results a straightforward method identifying collocational clues subjectivity, as well evidence the usefulness these recognizing opinionated documents.
参考文章(27)
A. P. Dawid, A. M. Skene, Maximum Likelihood Estimation of Observer Error‐Rates Using the EM Algorithm Journal of The Royal Statistical Society Series C-applied Statistics. ,vol. 28, pp. 20- 28 ,(1979) , 10.2307/2346806
Eduard Hovy, Combining and standardizing large- scale, practical ontologies for machine tranlation and other uses language resources and evaluation. pp. 535- 542 ,(1998)
Warren Sack, REPRESENTING AND RECOGNIZING POINT OF VIEW ,(1995)
Ellen Riloff, Rosie Jones, Learning dictionaries for information extraction by multi-level bootstrapping national conference on artificial intelligence. pp. 474- 479 ,(1999)
Douglas Biber, Co-occurrence patterns among collocations: a tool for corpus-based lexical knowledge acquisition Computational Linguistics. ,vol. 19, pp. 531- 538 ,(1993)
Janyce Wiebe, Learning Subjective Adjectives from Corpora national conference on artificial intelligence. pp. 735- 740 ,(2000)
Teun Adrianus van Dijk, News as Discourse ,(1990)
Monika Fludernik, The fictions of language and the languages of fiction ,(1993)
Janyce M. Wiebe, Tracking point of view in narrative Computational Linguistics. ,vol. 20, pp. 233- 287 ,(1994) , 10.5555/972525.972529
Mitch Marcus, Beatrice Santorini, Mary Ann Marcinkiewicz, None, Building a large annotated corpus of English: the penn treebank Computational Linguistics. ,vol. 19, pp. 313- 330 ,(1993) , 10.21236/ADA273556